ISSN 0081-4539




2010-11
          THE STATE
          OF FOOD
          AND
          AGRICULTURE




             WOMEN IN AGRICULTURE
            Closing the gender gap for development
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ISSN 0081-4539




2010-11
          THE STATE
          OF FOOD
          AND
          AGRICULTURE




          FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS
          Rome, 2011
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iii



Contents

Foreword	                                                                                         vi
Acknowledgements	                                                                                viii
Abbreviations and acronyms	                                                                        x

Part I
Women in agriculture: closing the gender gap for development	                                      1

1.		The gender gap in agriculture	                                                                 3
      Structure of the report and key messages	                                                    5
      Key messages of the report	                                                                  5
2.		 Women’s work	                                                                                 7
      Women in agriculture 	                                                                       7
      Women in rural labour markets	                                                              16
      Key messages	                                                                               22
3. 		 Documenting the gender gap in agriculture	                                                  23
      Land	                                                                                       23
      Livestock	                                                                                  24
      Farm labour	                                                                                26
      Education 	                                                                                 28
      Information and extension	                                                                  32
      Financial services	                                                                         33
      Technology	                                                                                 34
      Key messages 	                                                                              36
4.		 Gains from closing the gender gap	                                                           39
      Productivity of male and female farmers	                                                    40
      Production gains from closing the gender gap	                                               41
      Other social and economic benefits of closing the gender gap	                               43
      Key messages	                                                                               45
5.		 Closing the gender gap in agriculture and rural employment	                                  46
      Closing the gap in access to land	                                                          46
      Closing the gap in rural labour markets 	                                                   49
      Closing the financial services gap	                                                         51
      Closing the gap in social capital through women’s groups	                                   53
      Closing the technology gap 	                                                                56
      Key messages	                                                                               58
6. 		 Closing the gender gap for development	                                                     61

Part II
World food and agriculture in review	                                                            63

   Trends in undernourishment	                                                                   65
   Food production, consumption and trade during the crises	                                     68
   Recent trends in agricultural prices: a higher price plateau, and greater price volatility	   76
   Conclusions	                                                                                  81
iv


     PART III
     Statistical annex	                                                                        83

         Notes on the Annex tables	                                                             85
         TABLE A1	 Total population, female share of population and rural share of population
                    in 1980, 1995 and 2010	                                                     90
         TABLE A2	 Female share of national, rural and urban population aged 15–49,
                    most recent and earliest observations	                                      97
         TABLE A3	 Economically active population, female share of economically active
                    population and agricultural share of economically active women
                    in 1980, 1995 and 2010	                                                    104
         TABLE A4	 Economically active population, agricultural share of economically active
                    population and female share of economically active in agriculture
                    in 1980, 1995 and 2010	                                                    111
         TABLE A5	 Share of households in rural areas that are female-headed, most recent
                    and earliest observations, and total agricultural holders and female share
                    of agricultural holders, most recent observations	                         118
         Table A6	 Share of adult population with chronic energy deficiency (CED – body mass
                    index less than 18.5) by sex and share of children underweight by sex,
                    residence and household wealth quintile, most recent observations	         125



         References		                                                                         135
         Special chapters of The State of Food and Agriculture	                               146



     TABLES

     	   1.	 Employment in selected high-value agro-industries	                                21
     	   2.	 Selected examples of health insurance products targeted towards women	            52



     BOXES

     	   1.	    Sex versus gender 	                                                             4
     	   2.	    Frequently asked questions about women in agriculture 	                         8
     	   3.	    Women and unpaid household responsibilities	                                   14
     	   4.	    Female farmers, household heads and data limitations	                          24
     	   5.	    Labour productivity and hunger, nutrition and health 	                         27
     	   6.	    Women in agricultural higher education and research in Africa	                 30
     	   7.	    Smallholder coffee production and marketing in Uganda	                         37
     	   8.	    Targeting transfer payments to women for social benefits 	                     44
     	   9.	    Mama Lus Frut: working together for change	                                    47
     	   10.	   India’s Self Employed Women’s Association (SEWA) 	                             54
     	   11.	   Women in a sustainable rural livelihoods programme in Uganda	                  59
     	   12.	   Food emergencies 	                                                             70
     	   13.	   Implied volatility as a measure of uncertainty	                                79
     	   14.	   Price volatility and FAO’s Intergovernmental Groups on Grains and Rice	        81
v


FIGURES

	   1.	    Female share of the agricultural labour force	                                      10
	   2.	    Proportion of labour in all agricultural activities that is supplied by women	      11
	   3.	    Proportion of labour for selected crops that is supplied by women	                  12
	   4.	    Employment by sector	                                                               17
	   5. 	   Participation in rural wage employment, by gender	                                  18
	   6.	    Conditions of employment in rural wage employment, by gender	                       19
	   7.	    Wage gap between men and women in urban and rural areas	                            20
	   8.	    Share of male and female agricultural holders in main developing regions	           25
	   9.	    Rural household assets: farm size	                                                  25
	   10.	   Household livestock assets, in male- and female-headed households	                  26
	   11.	   Education of male and female rural household heads	                                 28
	   12.	   Gender differences in rural primary education attendance rates	                     29
	   13.	   Credit use by female- and male-headed households in rural areas	                    33
	   14.	   Fertilizer use by female- and male-headed households	                               35
	   15.	   Mechanical equipment use by female- and male-headed households	                     36
	   16.	   Cereal yield and gender inequality	                                                 39
	   17.	   Number of undernourished people in the world, 1969–71 to 2010	                      66
	   18.	   Proportion of population that is undernourished in developing regions,
           1969–71 to 2010	                                                                    66
	   19.	   Number of undernourished people in 2010, by region	                                 67
	   20.	   FAO Food Price Index in real terms, 1961–2010	                                      68
	   21.	   Average annual percentage change in GDP per capita at constant prices, 2005–2010	   69
	   22.	   Annual growth in global food production, consumption and trade, 2006–2010	          72
	   23.	   Indices of per capita food consumption by geographic region, 2000–10	               72
	   24.	   Indices of food production by economic group	                                       73
	   25.	   Indices of food production by region, 2000–10	                                      74
	   26.	   Indices of food export volumes by geographic region, 2000–10	                       75
	   27.	   Indices of food import volumes by geographic region, 2000–10	                       75
	   28.	   FAO Food Price Index and indices of other commodities (fruits, beverages and
           raw materials), October 2000–October 2010	                                          76
	   29.	   Indices of prices of commodities included in the FAO Food Price Index (cereals,
           oils, dairy, meat and sugar), October 2000–October 2010	                            77
	   30.	   Historic annualized volatility of international grain prices	                       78
	   31.	   Co-movement of energy production costs: ethanol from maize versus petrol
           from crude oil, October 2006–October 2010	                                          80
vi



     Foreword

     This edition of The State of Food and                The obstacles that confront women
     Agriculture addresses Women in agriculture:       farmers mean that they achieve lower yields
     closing the gender gap for development.           than their male counterparts. Yet women are
     The agriculture sector is underperforming in      as good at farming as men. Solid empirical
     many developing countries, and one of the         evidence shows that if women farmers used
     key reasons is that women do not have equal       the same level of resources as men on the
     access to the resources and opportunities         land they farm, they would achieve the same
     they need to be more productive. This             yield levels. The yield gap between men and
     report clearly confirms that the Millennium       women averages around 20–30 percent,
     Development Goals on gender equality              and most research finds that the gap is due
     (MDG 3) and poverty and food security             to differences in resource use. Bringing
     (MDG 1) are mutually reinforcing. We must         yields on the land farmed by women
     promote gender equality and empower               up to the levels achieved by men would
     women in agriculture to win, sustainably, the     increase agricultural output in developing
     fight against hunger and extreme poverty.         countries between 2.5 and 4 percent.
     I firmly believe that achieving MDG 3 can         Increasing production by this amount could
     help us achieve MDG 1.                            reduce the number of undernourished
        Women make crucial contributions in            people in the world in the order of
     agriculture and rural enterprises in all          12–17 percent. According to FAO’s latest
     developing country regions, as farmers,           estimates, 925 million people are currently
     workers and entrepreneurs. Their roles vary       undernourished. Closing the gender gap in
     across regions but, everywhere, women face        agricultural yields could bring that number
     gender-specific constraints that reduce their     down by as much as 100–150 million people.
     productivity and limit their contributions           These direct improvements in agricultural
     to agricultural production, economic              output and food security are just one part of
     growth and the well-being of their families,      the significant gains that could be achieved
     communities and countries.                        by ensuring that women have equal access
        Women face a serious gender gap in             to resources and opportunities. Closing
     access to productive resources. Women             the gender gap in agriculture would put
     control less land than men and the land           more resources in the hands of women and
     they control is often of poorer quality and       strengthen their voice within the household
     their tenure is insecure. Women own fewer         – a proven strategy for enhancing the food
     of the working animals needed in farming.         security, nutrition, education and health of
     They also frequently do not control the           children. And better fed, healthier children
     income from the typically small animals they      learn better and become more productive
     manage. Women farmers are less likely than        citizens. The benefits would span generations
     men to use modern inputs such as improved         and pay large dividends in the future.
     seeds, fertilizers, pest control measures and        The gender gap is manifest in other ways.
     mechanical tools. They also use less credit and   Gender relations are social phenomena
     often do not control the credit they obtain.      and it is impossible to separate women’s
     Finally, women have less education and less       economic spheres from their household
     access to extension services, which make it       activities. Preparing food and collecting
     more difficult to gain access to and use some     firewood and water are time-consuming and
     of the other resources, such as land, credit      binding constraints that must be addressed
     and fertilizer. These factors also prevent        if women are to be able to spend their time
     women from adopting new technologies as           in more rewarding and more productive
     readily as men do. The constraints women          ways. Interventions must consider women
     face are often interrelated and need to be        within their family and community contexts.
     addressed holistically.                           Making rural labour markets function better,
vii


providing labour-saving technologies and      would be significant. The basic principles
public goods and services, would enable       are clear. We must eliminate all forms of
women to contribute more effectively to,      discrimination against women under the
and benefit more fully from, the economic     law, ensure that access to resources is more
opportunities offered by agricultural         equal and that agricultural policies and
growth.                                       programmes are gender-aware, and make
  There exists no blueprint for closing the   women’s voices heard in decision-making
gender gap in agriculture, as a wide range    at all levels. Women must be seen as equal
of inputs, assets, services and markets are   partners in sustainable development.
involved and the related constraints are      Achieving gender equality and empowering
interlinked. But with appropriate policies    women is not only the right thing to do; it is
based on accurate information and analysis,   also crucial for agricultural development and
progress can be made and the benefits         food security.




                                                	                      Jacques Diouf
                                                	                  FAO DIRECTOR-GENERAL
viii



       Acknowledgements

       The State of Food and Agriculture 2010–11          Ruth Vargas Hill, Ephraim Nkonya, Amber
       was prepared by members of the Economic            Peterman, Esteban J. Quiñones and Agnes
       and Social Development Department of               Quisumbing, (IFPRI); Christopher Coles, Priya
       FAO under the overall leadership of Hafez          Deshingkar, Rebecca Holmes, Nicola Jones,
       Ghanem, Assistant Director-General, and            Jonathan Mitchell and Marcella Vigneri
       Kostas Stamoulis, Director of the Agricultural     (ODI); Diana Fletschner (Rural Development
       Development Economics Division (ESA).              Institute) and Lisa Kenney (University of
       Additional guidance was provided by Marcela        Washington); Christine Okali (University
       Villarreal, Director, and Eve Crowley, Principal   of East Anglia); Jan Lundius (independent
       Adviser, of the Gender, Equity and Rural           consultant); and Holger Seebens (KfW
       Employment Division (ESW); Pietro Gennari,         Entwicklungsbank). Additional background
       Director, Statistics Division (ESS); David         papers were prepared by the following FAO
       Hallam, Director, Trade and Markets Division       staff members: Gustavo Anríquez, Yasmeen
       (EST); and Keith Wiebe, Principal Officer, ESA.    Khwaja, Lucia Palombi (FAO Emergency
         The research and writing team for Part I         Operations and Rehabilitation Division) and
       was led by Terri Raney, André Croppenstedt         Paola Termine (ESW). The report also drew
       and Gustavo Anríquez and included Sarah            on papers prepared for the FAO-IFAD-ILO
       Lowder, Ira Matuschke and Jakob Skoet              Workshop on Gender and Rural Employment
       (ESA). Additional inputs were provided             and synthesized by Soline de Villard and
       by Luisa Cruz, Ana Paula de la O Campos,           Jennie Dey de Pryck. The report benefited
       Stefano Gerosa, Yasmeen Khwaja, Faith              from two expert consultations, partially
       Nilsson and Panagiotis Karfakis (ESA);             funded by the World Bank. In addition to
       Francesca Dalla Valle, Soline de Villard,          many of those mentioned above, external
       Caroline Dookie, John Curry, Zoraida Garcia,       participants included Isatou Jallow (WFP),
       Denis Herbel, Regina Laub, Maria Lee,              Johannes Jütting (OECD), Patricia Biermayr-
       Yianna Lambrou, Marta Osorio, Hajnalka             Jenzano (CIAT), Markus Goldstein and
       Petrics, Gabriel Rugalema, Libor Stloukal,         Eija Pehu (World Bank), Maria Hartl and
       Sophie Treinen and Peter Wobst (ESW);              Annina Lubbock (IFAD), Jemima Njuki (ILRI),
       Magdalena Blum (FAO Office of Knowledge            Thelma Paris (IRRI), Patrick Webb (Tufts
       Exchange, Research and Extension); Holger          University), and Manfred Zeller (University of
       Matthey (EST); Anni McLeod and Frauke              Hohenheim). Hela Kochbati (Afard), Robert
       Kramer (FAO Animal Production and Health           Mazur (Iowa State University) and others
       Division); Helga Josupeit, Rebecca Metzner         made valuable contributions to the Global
       and Stefania Vannuccini (FAO Fisheries             Forum on Food Security and Nutrition (FSN
       and Aquaculture Policy and Economic                Forum) on Women in Agriculture, organized
       Division); Robert Mayo (ESS) and Diana             by Max Blanck and Renata Mirulla (ESA).
       Tempelman (FAO Regional Office for Africa).        We are grateful for many useful comments
       Ines Smyth (Oxfam), Cathy Farnworth (on            received at a mini-symposium organized at
       behalf of IFAD), Elisenda Estruch (ESW)            the International Association of Agricultural
       and Julian Thomas and Frank Mischler               Economists Triennial Conference.
       (ESA) provided valuable comments. We are              In addition, the final draft report was
       also grateful to Amy Heyman who read,              reviewed by Patrick Webb (Tufts University),
       commented and edited the first draft of            Diana Fletschner (Rural Development
       the report. The report was prepared in             Institute), Thomas P. Thompson (IFDC),
       close collaboration with Agnes Quisumbing          Maria Hartl (IFAD), Carmen Diana Deere
       and Ruth Meinzen-Dick of IFPRI and Cheryl          (UCLA), Susana Lastarria-Corhiel (University
       Doss of Yale University. Background papers,        of Wisconsin), Jo Swinnen (University of
       partially funded by ESW, were prepared by          Leuven), Patricia Biermayr-Jenzano, Joanne
       Cheryl Doss; Julia Behrman, Andrew Dillon,         Sandler and colleagues (UNIFEM), Barbara
ix


Stocking (Oxfam GB), Paul Munro-Faure          Ramasawmy, Mukesh Srivastava, and Franco
and Paul Mathieu (FAO Climate, Energy and      Stefanelli (ESS); Diana Tempelman; Maria
Tenure Division), Ruth Meinzen-Dick (IFPRI),   Adelaide D’Arcangelo, Zoraida Garcia and
Agnes Quisumbing (IFPRI), and Cheryl Doss      Clara Park (ESW), and Barbara Burlingame
(Yale University). The writing team is most    and Marie-Claude Dop (FAO Nutrition and
grateful to the workshop participants and      Consumer Protection Division).
other internal and external reviewers of         The publication was greatly enhanced
various drafts of the manuscript.              by Michelle Kendrick (ESA) who provided
  Part II of the report was jointly authored   English editorial and project management
by Sarah Lowder (ESA) and Holger Matthey       support. Liliana Maldonado and Paola
and Merritt Cluff (EST), under the guidance    di Santo (ESA) provided excellent
of Jakob Skoet. Additional inputs were         administrative support throughout the
provided by Joshua Dewbre and Kisan Gunjal     process. Translations and printing services
(EST).                                         were provided by the Meeting Programming
  Part III of the report was prepared by       and Documentation Service of the FAO
Sarah Lowder, with assistance from Brian       Corporate Services, Human Resources and
Carisma and Stefano Gerosa, under the          Finance Department. Graphic, layout and
guidance of Terri Raney. Helpful comments      proofing services were provided by Flora
were provided by Naman Keita, Seevalingum      Dicarlo and Visiontime.
x



    Abbreviations and acronyms

    CED	      chronic energy deficiency

    CIAT	     International Centre for Tropical Agriculture

    FFS	      Farmer field school

    FPI	      Food Price Index (FAO)

    ICTs	     information and communication technologies

    IFAD	     International Fund for Agricultural Development

    IFDC	     International Fertilizer Development Center

    IFPRI	    International Food Policy Research Institute

    ILRI	     International Livestock Research Institute

    IMF	      International Monetary Fund

    LSMS	     Living Standards Measurement Study

    MDG	      Millennium Development Goal

    NGOs	     non-governmental organizations

    NREGA	    National Rural Employment Guarantee Act (India)

    ODI	      Overseas Development Institute (United Kingdom)

    OECD	     Organisation for Economic Co-operation and Development

    RIGA	     Rural Income Generating Activities

    SIGI	     Social Institutions and Gender Inequality

    UCLA	     University of California, Los Angeles (United States of America)

    UNDP	     United Nations Development Programme

    UNIFEM	   United Nations Development Fund for Women

    WFP	      World Food Programme
Part I
                  WOMEN
           IN AGRICULTURE
Closing the gender gap for development
Part I
W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t

                                                                                                                                    3


1.	 The gender gap in agriculture


Agriculture is underperforming in many               As a result, it is often assumed that
developing countries for a number of                 interventions in areas such as technology,
reasons. Among these is the fact that women          infrastructure and market access have the
lack the resources and opportunities they            same impacts on men and women, when in
need to make the most productive use of              fact they may not.
their time. Women are farmers, workers                  At the same time, building a gender
and entrepreneurs, but almost everywhere             perspective into agricultural policies and
they face more severe constraints than               projects has been made to seem more
men in accessing productive resources,               difficult and complex than it need be.
markets and services. This “gender gap”              Clarification of what is meant by gender is a
hinders their productivity and reduces their         good place to start (Box 1).
contributions to the agriculture sector and to          The last sentence in Box 1 also gives room
the achievement of broader economic and              for hope: gender roles can change. It is the
social development goals. Closing the gender         goal of this report that it will contribute to
gap in agriculture would produce significant         improving understanding so that appropriate
gains for society by increasing agricultural         policies can help foster gender equality,
productivity, reducing poverty and hunger            even as agriculture itself is changing.
and promoting economic growth.                       The agriculture sector is becoming more
   Governments, donors and development               technologically sophisticated, commercially
practitioners now recognize that agriculture         oriented and globally integrated; at the
is central to economic growth and food               same time, migration patterns and climate
security – particularly in countries where a         variability are changing the rural landscape
significant share of the population depends          across the developing world. These forces
on the sector – but their commitment to              pose challenges and present opportunities for
gender equality in agriculture is less robust.       all agricultural producers, but women face
Gender issues are now mentioned in most              additional legal and social barriers that limit
national and regional agricultural and               their ability to adapt to and benefit from
food-security policy plans, but they are             change. Governments and donors have made
usually relegated to separate chapters on            major commitments aimed at revitalizing
women rather than treated as an integral             agriculture in developing regions, but their
part of policy and programming. Many                 efforts in agriculture will yield better results
agricultural policy and project documents            more quickly if they maximize the productive
still fail to consider basic questions about the     potential of women by promoting gender
differences in the resources available to men        equality.
and women, their roles and the constraints              Women, like men, can be considered
they face – and how these differences might          “productive resources”, but they are also
be relevant to the proposed intervention.            citizens who have an equal claim with men
4   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




               BOX 1
               Sex versus gender


               The concepts of “sex” and “gender”                       men and women (Moser, 1989). Being
               can be confusing, not least because                      socially determined, however, this
               even the experts sometimes use them                      distribution can be changed through
               inconsistently. Sex refers to the innate                 conscious social action, including public
               biological categories of male or female.                 policy. Every society is marked by gender
               Gender refers to the social roles and                    differences, but these vary widely by
               identities associated with what it means                 culture and can change dramatically over
               to be a man or a woman. Gender roles are                 time. Sex is biology. Gender is sociology.
               shaped by ideological, religious, ethnic,                Sex is fixed. Gender roles change.
               economic and cultural factors and are a
               key determinant of the distribution of
               responsibilities and resources between                   Source: Quisumbing, 1996.



            on the protections, opportunities and                       empirical evidence from many different
            services provided by their governments                      countries shows that female farmers are just
            and the international community. Gender                     as efficient as their male counterparts, but
            equality is a Millennium Development Goal                   they have less land and use fewer inputs, so
            (MDG) in its own right, and it is directly                  they produce less. The potential gains that
            related to the achievement of the MDG                       could be achieved by closing the gender
            targets on reducing extreme poverty and                     gap in input use are estimated in this report
            hunger. Clear synergies exist between the                   in terms of agricultural yields, agricultural
            gender-equality and hunger-reduction goals.                 production, food security and broader
            Agricultural policy-makers and development                  aspects of economic and social welfare.
            practitioners have an obligation to ensure                     Because many of the constraints faced by
            that women are able to participate fully in,                women are socially determined, they can
            and benefit from, the process of agricultural               change. What is more, external pressures
            development. At the same time, promoting                    often serve as a catalyst for women to take
            gender equality in agriculture can help                     on new roles and responsibilities that can
            reduce extreme poverty and hunger. Equality                 improve their productivity and raise their
            for women would be good for agricultural                    status within households and communities.
            development, and agricultural development                   For example, the growth of modern supply
            should also be good for women.                              chains for high-value agricultural products
              The roles and status of women in                          is creating significant opportunities – and
            agriculture and rural areas vary widely                     challenges – for women in on-farm and off-
            by region, age, ethnicity and social class                  farm employment. Other forces for social
            and are changing rapidly in some parts                      and economic change can also translate into
            of the world. Policy-makers, donors and                     opportunities for women.
            development practitioners need information                     Gender-aware policy support and well-
            and analysis that reflect the diversity of the              designed development projects can help
            contributions women make and the specific                   close the gender gap. Given existing
            challenges they are confronted with in order                inequities, it is not enough that policies be
            to make gender-aware decisions about the                    gender-neutral; overcoming the constraints
            sector.                                                     faced by women requires much more.
              Despite the diversity in the roles and                    Reforms aimed at eliminating discrimination
            status of women in agriculture, the evidence                and promoting equal access to productive
            and analysis presented in this report confirm               resources can help ensure that women – and
            that women face a surprisingly consistent                   men – are equally prepared to cope with
            gender gap in access to productive assets,                  the challenges and to take advantage of
            inputs and services. A large body of                        the opportunities arising from the changes
W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t

                                                                                                                                  5
shaping the rural economy. Closing the             farmers and estimates the gains that could
gender gap in agriculture will benefit             be achieved by closing the gender gap in
women, the agriculture and rural sectors,          agricultural input use. Potential gains in
and society as a whole. The gains will vary        agricultural yields, agricultural production,
widely according to local circumstances, but       food security and broader aspects of
they are likely to be greater where women          economic and social welfare are assessed.
are more involved in agriculture and face the        Chapter 5 advances specific policies and
most severe constraints.                           programmes that can help close the gender
  While it seems obvious that closing the          gap in agriculture and rural employment.
gender gap would be beneficial, evidence           The focus is on interventions that alleviate
to substantiate this potential has been            constraints on agricultural productivity and
lacking. This edition of The State of Food         rural development.
and Agriculture has several goals: to bring          Chapter 6 provides broader
the best available empirical evidence to           recommendations for closing the gender gap
bear on the contributions women make and           for development.
the constraints they face in agricultural and
rural enterprises in different regions of the
world; to demonstrate how the gender gap           Key messages of the report
limits agricultural productivity, economic
development and human well-being; to                  •	 Women make essential contributions to
evaluate critically interventions aimed at               agriculture in developing countries, but
reducing the gender gap and to recommend                 their roles differ significantly by region
practical steps that national governments                and are changing rapidly in some areas.
and the international community can take                 Women comprise, on average, 43 percent
to promote agricultural development by                   of the agricultural labour force in
empowering women.                                        developing countries, ranging from
                                                         20 percent in Latin America to 50 percent
                                                         in Eastern Asia and sub-Saharan Africa.
Structure of the report and key                          Their contribution to agricultural work
messages                                                 varies even more widely depending on
                                                         the specific crop and activity.
Chapter 2 provides a survey of the roles              •	 Women in agriculture and rural areas
and status of women in agriculture and                   have one thing in common across
rural areas in different parts of the world.             regions: they have less access than
It brings the best, most comprehensive                   men to productive resources and
available evidence to bear on a number                   opportunities. The gender gap is found
of controversial questions that are both                 for many assets, inputs and services
conceptually and empirically challenging.                – land, livestock, labour, education,
It focuses on women’s contributions                      extension and financial services, and
as farmers and agricultural workers                      technology – and it imposes costs on the
and examines their status in terms of                    agriculture sector, the broader economy
poverty, hunger and nutrition, and rural                 and society as well as on women
demographics. It also looks at the ways in               themselves.
which the transformation of agriculture and           •	 Closing the gender gap in agriculture
the emergence of high-value marketing                    would generate significant gains for
chains are creating challenges and                       the agriculture sector and for society.
opportunities for women.                                 If women had the same access to
   Chapter 3 documents the constraints                   productive resources as men, they
facing women in agriculture across a range               could increase yields on their farms by
of assets: land, livestock, farm labour,                 20–30 percent. This could raise total
education, extension services, financial                 agricultural output in developing
services and technology.                                 countries by 2.5–4 percent, which could
   Chapter 4 surveys the economic evidence               in turn reduce the number of hungry
on the productivity of male and female                   people in the world by 12–17 percent.
6   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                  The potential gains would vary by region                 resources, education, extension and
                  depending on how many women are                          financial services, and labour markets;
                  currently engaged in agriculture, how                 -- investing in labour-saving and
                  much production or land they control,                    productivity-enhancing technologies
                  and how wide a gender gap they face.                     and infrastructure to free women’s
               •	 Policy interventions can help close the                  time for more productive activities;
                  gender gap in agriculture and rural labour               and
                  markets. Priority areas for reform include:           -- facilitating the participation of women
                  -- eliminating discrimination against                    in flexible, efficient and fair rural
                     women in access to agricultural                       labour markets.
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                                                                                                                                                7
2.	 Women’s work


Women make essential contributions to                            participation in the labour force has a
agriculture and rural economic activities in                     positive impact on economic growth (Klasen
all developing country regions.1 Their roles                     and Lamanna, 2009).
vary considerably among and within regions
and are changing rapidly in many parts
of the world where economic and social                           Women in agriculture
forces are transforming the agriculture
sector. The emergence of contract farming                        Women work in agriculture as farmers on
and modern supply chains for high-value                          their own account, as unpaid workers on
agricultural products, for example, present                      family farms and as paid or unpaid labourers
different opportunities and challenges                           on other farms and agricultural enterprises.
for women than they do for men. These                            They are involved in both crop and livestock
differences derive from the different roles                      production at subsistence and commercial
and responsibilities of women and the                            levels. They produce food and cash crops and
constraints that they face.                                      manage mixed agricultural operations often
   Rural women often manage complex                              involving crops, livestock and fish farming.
households and pursue multiple livelihood                        All of these women are considered part of
strategies. Their activities typically include                   the agricultural labour force.2
producing agricultural crops, tending                               Based on the latest internationally
animals, processing and preparing food,                          comparable data, women comprise an
working for wages in agricultural or other                       average of 43 percent of the agricultural
rural enterprises, collecting fuel and water,                    labour force of developing countries. The
engaging in trade and marketing, caring                          female share of the agricultural labour
for family members and maintaining their                         force ranges from about 20 percent in Latin
homes (see Box 2 for some of the frequently                      America to almost 50 percent in Eastern and
asked questions on the roles and status                          Southeastern Asia and sub-Saharan Africa
of women in agriculture). Many of these                          (Figure 1). The regional averages in Figure
activities are not defined as “economically                      1 mask wide variations within and among
active employment” in national accounts                          countries (see Annex tables A3 and A4).
but they are all essential to the well-being                        Women in sub-Saharan Africa have
of rural households (see Box 3, page 14,                         relatively high overall labour-force
for a discussion of women’s household                            participation rates and the highest average
responsibilities).                                               agricultural labour-force participation
   Women often face gender-specific                              rates in the world. Cultural norms in the
challenges to full participation in the                          region have long encouraged women to be
labour force, which may require policy                           economically self-reliant and traditionally
interventions beyond those aimed at                              give women substantial responsibility for
promoting economic growth and the                                agricultural production in their own right.
efficiency of rural labour markets. Policies                     Regional data for sub-Saharan Africa conceal
can influence the economic incentives                            wide differences among countries. The share
and social norms that determine whether                          of women in the agricultural labour force
women work, the types of work they
perform and whether it is considered an                          2	
                                                                    The agricultural labour force includes people who are
economic activity, the stock of human                            working or looking for work in formal or informal jobs and
capital they accumulate and the levels                           in paid or unpaid employment in agriculture. That includes
                                                                 self-employed women as well as women working on family
of pay they receive. Increasing female
                                                                 farms. It does not include domestic chores such as fetching
                                                                 water and firewood, preparing food and caring for children
1	
     The material in this chapter is based on FAO (2010a).       and other family members.
8   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




               BOX 2
               Frequently asked questions about women in agriculture


               Question 1: How much of the agricultural                 Question 3: Do women have less access
               labour in the developing world is                        than men to agricultural resources and
               performed by women?                                      inputs?
               Answer: Women comprise 43 percent                        Answer: Yes, this is one generalization
               of the agricultural labour force, on                     about women in agriculture that holds
               average, in developing countries; this                   true across countries and contexts:
               figure ranges from around 20 percent in                  compared with their male counterparts,
               Latin America to 50 percent in parts of                  female farmers in all regions control less
               Africa and Asia, but it exceeds 60 percent               land and livestock, make far less use of
               in only a few countries (FAO, 2010a).                    improved seed varieties and purchased
               Critics argue that labour force statistics               inputs such as fertilizers, are much less
               underestimate the contribution of women                  likely to use credit or insurance, have
               to agricultural work because women                       lower education levels and are less likely
               are less likely to declare themselves as                 to have access to extension services (see
               employed in agriculture and they work                    Chapter 3).
               longer hours than men (Beneria, 1981),
               but evidence from time-use surveys does                  Question 4: Do women and girls comprise
               not suggest that women perform most of                   the majority of the world’s poor people?
               the agricultural labour in the developing                Answer: Poverty is normally measured
               world (see Chapter 2).                                   in terms of income or consumption at
                                                                        the household level, not for individuals,
               Question 2: What share of the world’s                    so separate poverty rates for men and
               food is produced by women?                               women cannot be calculated. Females
               Answer: This question cannot be answered                 could be overrepresented among the
               in any empirically rigorous way because                  poor if female-headed households are
               of conceptual ambiguities and data                       poorer than male-headed households
               limitations. Different definitions of “food”             (see Question 6) or if significant anti-
               and “production” would yield different                   female bias exists within households (see
               answers to the question and, more                        Question 7). Females may be poorer than
               importantly, food production requires                    males if broader measures of poverty are
               many resources – land, labour, capital –                 considered, such as access to productive
               controlled by men and women who work                     resources (see Question 3).
               cooperatively in most developing countries,
               so separating food production by gender is               Question 5: Do women face discrimination
               not very meaningful (Doss, 2010).                        in rural labour markets?



            ranges from 36 percent in Côte d’Ivoire and                 where the female share of the agricultural
            the Niger to over 60 percent in Lesotho,                    labour force has increased slightly since 1980
            Mozambique and Sierra Leone. A number of                    to almost 48 percent. The share of women
            countries have seen substantial increases in                in the agricultural labour force in most
            the female share of the agricultural labour                 other countries in the region has remained
            force in recent decades due to a number                     fairly steady at between 40 and 50 percent,
            of reasons, including conflict, HIV/AIDS and                although it is substantially lower and
            migration.                                                  declining in some countries such as Malaysia
              Women in Eastern and Southeastern Asia                    and the Philippines.
            also make very substantial contributions to                   The Southern Asian average is dominated
            the agricultural labour force, almost as high               by India, where the share of women in the
            on average as in sub-Saharan Africa. The                    agricultural labour force has remained steady
            regional average is dominated by China,                     at just over 30 percent. This masks changes
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  Answer: In most countries and in keeping          Question 7: Are women and girls
  with global figures, women in rural areas         more likely than men and boys to be
  who work for wages are more likely than           undernourished?
  men to hold seasonal, part-time and low-          Answer: A positive answer to this
  wage jobs and (controlling for education,         statement is not supported by available
  age and industry) women receive lower             evidence, and generalizations are difficult
  wages for the same work (see Chapter 2).          to make. The limited evidence available
                                                    suggests that this may be true in Asia,
  Question 6: Are female-headed                     while it is not true in Africa. More sex-
  households the poorest of the poor?               disaggregated data of better quality on
  Answer: Data from 35 nationally                   anthropometric and other indicators of
  representative surveys for 20 countries           malnutrition are needed to arrive at clear
  analysed by FAO show that female-                 conclusions. There is, however, evidence
  headed households are more likely to be           that girls are much more vulnerable to
  poor than male-headed households in               transitory income shocks than boys (Baird,
  some countries but the opposite is true           Friedman and Schady, 2007).
  in other countries – so it is not possible to
  generalize. Data limitations also make it         Question 8: Are women more likely than
  impossible to distinguish systematically          men to spend additional income on their
  between households headed by women                children?
  who are single, widowed or divorced (de           Answer: A very large body of research
  jure female heads) and those who are              from many countries around the world
  associated with an adult male who supports        confirms that putting more income in
  the family through remittances and social         the hands of women yields beneficial
  networks (de facto female heads). It is           results for child nutrition, health and
  likely that the former are more likely to         education. Other measures – such as
  be poor than the latter (Anríquez, 2010).         improving education – that increase
  There is also evidence to suggest that rural      women’s influence within the household
  female-headed households were more                are also associated with better outcomes
  vulnerable than males during the food price       for children. Exceptions exist, of course,
  shock of 2008 because they spend a larger         but empowering women is a well-proven
  proportion of household income on food            strategy for improving children’s well-
  and because they were less able to respond        being (see Chapter 4).
  by increasing food production (Zezza et al.,
  2008). Again, these results vary by country.



in other countries where the female share           participation in the region are found in
of the agricultural labour force appears to         Jordan, the Libyan Arab Jamahiriya and the
have increased dramatically, such as Pakistan       Syrian Arab Republic.
where it has almost tripled since 1980, to            The countries of Latin America have high
30 percent, and Bangladesh where women              overall female labour-force participation
now exceed 50 percent of the agricultural           rates, but much lower participation in
labour force.                                       agriculture than those in other developing
  The female share of the agricultural labour       country regions. This pattern reflects
force in the Near East and North Africa             relatively high female education levels
appears to have risen substantially, from           (see Chapter 4), economic growth and
30 percent in 1980 to almost 45 percent.            diversification, and cultural norms that
Some of the highest and fastest-growing             support female migration to service jobs
rates of female agricultural labour force           in urban areas. Just over 20 percent of the
10   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                   FIGURE 1
                   Female share of the agricultural labour force

                   Percentage
                   60

                   50

                   40

                   30

                   20

                   10

                    0
                     1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010


                              Eastern and Southeastern Asia                    Latin America and the Caribbean
                              Near East and North Africa                       Southern Asia
                              Sub-Saharan Africa

             Note: The female share of the agricultural labour force is calculated as the total number of women economically active
             in agriculture divided by the total population economically active in agriculture. Regional averages are weighted
             by population.
             Source: FAO, 2010b. See Annex table A4.


             agricultural labour force in Latin America                      Time-use surveys attempt to provide a
             was female in 2010, slightly higher than                     complete account of how men and women
             in 1980. The South American countries of                     allocate their time.3 Such studies generally
             the Plurinational State of Bolivia, Brazil,                  are not nationally representative and are
             Colombia, Ecuador and Peru dominate both                     not directly comparable because they usually
             the average and the rising trend, while                      cover small samples, report on different
             many countries in Central America and the                    types of activities (that are not always clearly
             Caribbean have seen declining shares of                      specified) and use different methodologies.
             women in the agricultural labour force.                      Despite these caveats, a summary of the
                Although in some countries sex-                           evidence from studies that specify time use
             disaggregated data collection has improved                   by agricultural activity suggests interesting
             over recent decades, some researchers                        patterns.
             have raised concerns as to the validity of                      Time-use surveys that cover all agricultural
             agricultural labour-force statistics as a                    activities (Figure 2) reveal considerable
             measure of women’s work in agriculture                       variation across countries, and sometimes
             (Beneria, 1981; Deere, 2005). Women’s                        within countries, but the data are broadly
             participation in the agricultural labour force               similar to the labour force statistics discussed
             may underestimate the amount of work                         above. In Africa, estimates of the time
             women do because women are less likely                       contribution of women to agricultural
             than men to define their activities as work,
             they are less likely to report themselves                    3
                                                                           	 It is commonly claimed that women perform
             as being engaged in agriculture and they                     60–80 percent of the agricultural labour in developing
             work, on average, longer hours than men                      countries (UNECA, 1972; World Bank, FAO and IFAD,
                                                                          2009). The evidence from time-use surveys and agricultural
             – so even if fewer women are involved                        labour-force statistics does not support this general
             they may contribute more total time to the                   statement, although women do comprise over 60 percent
             sector.                                                      of the agricultural labour force in some countries.
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     FIGURE 2
     Proportion of labour in all agricultural activities that is supplied by women


                           Gambia

    United Republic of Tanzania

                     Burkina Faso

                            Nigeria

                        Zambia (1)

                        Zambia (2)

      Cameroon (Centre–South)

    Cameroon (Yassa of Campo,
                   Southwest)
    Cameroon (Mvae of Campo,
                   Southwest)

                              Niger

                              Togo

                            Ghana

               India/West Bengal

                              India

                  India/Rajasthan

                             Nepal

                             China

                           Peru (1)

                           Peru (2)

                                      0       10       20        30        40        50        60        70        80
                                                    Percentage of labour supplied by women


                           Africa                           Asia                          Latin America

Note: Only the survey for India is nationally representative.
Sources (from top to bottom): Gambia: von Braun and Webb, 1989; United Republic of Tanzania: Fontana and Natali, 2008;
Burkina Faso: Saito, Mekonnen and Spurling, 1994; Nigeria: Rahji and Falusi, 2005; Zambia (1): Saito, Mekonnen and
Spurling, 1994; Zambia (2): Kumar, 1994; Cameroon, Centre–South: Leplaideur, 1978, cited by Charmes, 2006: Cameroon
(Yasssa of Campo, Southwest): Charmes, 2006, based on Pasquet and Koppert, 1993 and 1996; Cameroon (Mvae of Campo,
Southwest): Charmes, 2006, based on Pasquet and Koppert, 1993 and 1996; Niger: Baanante, Thompson and Acheampong,
1999; Togo: Baanante, Thompson and Acheampong, 1999; Ghana: Baananate, Thompson and Acheampong, 1999; India
(West Bengal): Jain, 1996; India: Singh and Sengupta, 2009; India (Rajasthan): Jain, 1996; Nepal: Joshi, 2000; China: de
Brauw et al., 2008; Peru (1): Deere, 1982; Peru (2): Jacoby, 1992.
12   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




             activities ranges from about 30 percent in                         is a predominantly female activity, but
             the Gambia to 60–80 percent in different                           women are typically involved to some extent
             parts of Cameroon. In Asia, estimates range                        in all activities except ploughing.
             from 32 percent in India to over 50 percent                           Studies from Indonesia reveal greater
             in China. The range is lower in Latin America,                     involvement of women in upland rice
             but exceeds 30 percent in some parts of Peru.                      production than that of wet rice and in the
             A striking degree of within-country variation                      management of young plantation crops
             is shown by the study for India. While this                        such as cinnamon and rubber rather than
             nationally representative study indicates that                     the same crops at maturity. As noted above,
             the national average for women’s share of                          the data for India hide wide variations
             total time-use in agriculture is 32 percent,                       between West Bengal and Rajasthan, but
             the share ranges from less than 10 percent                         in both areas, younger women contribute
             in West Bengal to more than 40 percent in                          a higher share of the total time provided
             Rajasthan.                                                         in agriculture by their age group than
                These studies also reveal that female time-                     older women do in theirs. In Rajasthan,
             use in agriculture varies widely depending                         for example, girls aged between 14 and 19
             on the crop and the phase of the production                        contribute up to 60 percent of the total time
             cycle, the age and ethnic group of the                             spent on agriculture by their age group (Jain,
             women in question, the type of activity and                        1996). Two separate studies are reported
             a number of other factors (Figure 3). Planting                     each for Peru and Zambia, and differences


                   FIGURE 3
                   Proportion of labour for selected crops that is supplied by women


                        Young rubber

                       Mature rubber

                    Young cinnamon

                   Mature cinnamon

                               Wet rice

                           Upland rice

                                     Rice

                                     Rice

                                     Rice

                              Tomatoes

                                            0         10          20       30         40      50       60       70        80

                                                             Percentage of labour supplied by women


                                      Indonesia                          Bangladesh                      Philippines

                                      Viet Nam                           Dominican Republic

            Sources (from top to bottom): Indonesia (young rubber): Quisumbing and Otsuka, 2001a; Indonesia (mature rubber):
            Quisumbing and Otsuka, 2001a; Indonesia (young cinnamon): Quisumbing and Otsuka, 2001a; Indonesia (mature cinnamon):
            Quisumbing and Otsuka, 2001a; Indonesia (wet rice): Quisumbing and Otsuka, 2001a; Indonesia (upland rice): Quisumbing
            and Otsuka, 2001a; Bangladesh: Thompson and Sanabria, 2010; Philippines: Estudillo, Quisumbing and Otsuka, 2001;
            Viet Nam: Paris and Chi, 2005; Dominican Republic: Raynolds, 2002.
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reflect different time periods and locations                     Evidence shows, however, that female
within the countries.                                          farmers are largely excluded from modern
   Time-use studies permit a rich analysis                     contract-farming arrangements because they
of what men and women do in agriculture                        lack secure control over land, family labour
and how their roles may differ by crop,                        and other resources required to guarantee
location, management structure, age and                        delivery of a reliable flow of produce. For
ethnic group. They offer policy-relevant                       example, women comprise fewer than
information about where, when and how                          10 percent of the farmers involved in
to target interventions aimed at women                         smallholder contract-farming schemes in
and how to bring men into the process                          the Kenyan fresh fruit and vegetable export
constructively. Given the variation in gender                  sector (Dolan, 2001), and only 1 of a sample
roles in agriculture, generalizations about                    of 59 farmers contracted in Senegal to
time use from one region to another are                        produce French beans for the export sector
not appropriate. Studies that consider the                     was a woman (Maertens and Swinnen, 2009).
gender roles within their specific geographic                    While men control the contracts, however,
and cultural context can provide practical                     much of the farm work done on contracted
guidance for policy-makers and practitioners                   plots is performed by women as family
involved in technology investments,                            labourers. For example, in 70 percent of the
extension services, post-harvest activities and                cases of sugar contract-farming in South
marketing interventions.                                       Africa, the principal farmer on the sugar-
   One generalization that does hold is                        cane plots is a woman (Porter and Philips-
that women usually allocate time to food                       Horward, 1997). Women work longer hours
preparation, child care and other household                    than men in vegetable contract-farming
responsibilities in addition to the time                       schemes controlled by male farmers in
they spend in agriculture (see Box 3). In                      the Indian Punjab (Singh, 2003). In a large
most societies, household responsibilities                     contract-farming scheme involving thousands
are divided along gender lines, although                       of farmers in China, women – while excluded
these norms differ by culture and over time.                   from signing contracts themselves – perform
Depending on the household structure and                       the bulk of the work related to contract
size, these tasks may be extremely time-                       farming (Eaton and Shepherd, 2001). Women
intensive. Across regions, time allocation                     may not be well compensated as unpaid
studies have shown that women work                             family labour in contract-farming schemes
significantly more than men if care-giving is                  (Maertens and Swinnen, 2009).
included in the calculations (Ilahi, 2000). The                  Evidence is mixed regarding whether
combination of commitments often means                         contract farming increases overall household
that women are more time-constrained than                      incomes or creates conflicts between the
men (Blackden and Wodon, 2006).                                production of cash crops and food crops.
                                                               For example, Dolan (2001) argues that the
Women in modern contract-farming4                              growth of high-value horticulture supply
One noteworthy feature of modern                               chains has been detrimental for rural
agricultural value chains is the growth of                     women in Kenya because land and labour
contract farming or out-grower schemes for                     resources that were traditionally used by
high-value produce through which large-                        women to cultivate vegetables for home
scale agroprocessing firms seek to ensure                      consumption and sale in local markets
a steady supply of quality produce. Such                       have been appropriated by men for export
schemes can help small-scale farmers and                       vegetable production under contract. On
livestock producers overcome the technical                     the other hand, although their results are
barriers and transaction costs involved in                     not gender-specific, Minten, Randrianarison
meeting the increasingly stringent demands                     and Swinnen (2009), find that high-value
of urban consumers in domestic and                             vegetable contract-farming in Madagascar
international markets.                                         leads to improved productivity for food (rice)
                                                               production through technology spillovers,
4
 	 The material in this section is based on Maertens and       thereby improving the availability of food
Swinnen (2009).                                                in the household and shortening the lean
14   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                BOX 3
                Women and unpaid household responsibilities


                Women have primary responsibilities for                    Because of the gender-specific
                household and child-rearing activities                   assignment of tasks, any change affecting
                in most societies, although norms differ                 the family or the environment may
                by culture and are changing over time.                   have different implications for men and
                Time-use surveys across a wide range of                  women. HIV/AIDS, for example, has caused
                countries estimate that women provide                    a significant increase in the time needed
                85–90 percent of the time spent on                       to care for sick family members or the
                household food preparation and that                      orphaned children of relatives (Addati
                they are also usually responsible for child              and Cassirer, 2008). Deforestation leads
                care and other household chores. The                     women to travel increasing distances from
                combined time burden of household                        the homestead to collect firewood (Kumar
                chores and farm work is particularly severe              and Hotchkiss, 1988; Nankhuni, 2004).
                for women in Africa (Ilahi, 2000).                         Poor infrastructure and limited provision
                   Ghanaian women carry a much heavier                   of public services require Tanzanian
                burden for household chores despite                      women in rural areas to spend long
                working outside the home almost as much                  hours on water and fuel collection, food
                as men (Brown, 1994). In Uganda, women                   preparation and other domestic and
                cite the time they spend looking after                   child-care activities. Improving public
                their families, working in their husbands’               infrastructure for water and fuel collection
                gardens and producing food for their                     and food preparation (e.g. grain-milling
                households as reasons for their inability to             facilities) could free women in the United
                expand production for the market (Ellis,                 Republic of Tanzania from a burden that
                Manuel and Blackden, 2006). Women and                    represents 8 billion hours of unpaid work
                girls in Ghana, the United Republic of                   per year, which is equivalent to the hours
                Tanzania and Zambia are responsible for                  required for 4.6 million full-time jobs. The
                about 65 percent of all transport activities             same improvements would save time for
                in rural households, such as collecting                  men also, but less: the time-equivalent of
                firewood and water and carrying grain to                 200 000 full-time jobs (Fontana and Natali,
                the grinding mill (Malmberg-Calvo, 1994).                2008).



            period or “hunger season”. Maertens and                      engaged in the sector. An estimated two-
            Swinnen (2009) do not find evidence of                       thirds of poor livestock keepers, totalling
            gender conflict over resources in the French                 approximately 400 million people, are
            bean export sector in Senegal because                        women (Thornton et al., 2002). They share
            households only allocate part of their land                  responsibility with men and children for the
            and labour resources to bean production,                     care of animals, and particular species and
            which occurs during the off-season and does                  types of activity are more associated with
            not coincide with the main rainy season                      women than men. For example, women
            when staple food crops and other subsistence                 often have a prominent role in managing
            crops are cultivated.                                        poultry (FAO, 1998; Guèye, 2000; Tung,
                                                                         2005) and dairy animals (Okali and Mims,
            Women as livestock keepers5                                  1998; Tangka, Jabbar and Shapiro, 2000)
            Within pastoralist and mixed farming                         and in caring for other animals that are
            systems, livestock play an important role in                 housed and fed within the homestead.
            supporting women and in improving their                      When tasks are divided, men are more
            financial situation, and women are heavily                   likely to be involved in constructing housing
                                                                         and the herding of grazing animals, and
                                                                         in marketing products if women’s mobility
            5	
               The material in this section was prepared by FAO’s
            Agriculture and Consumer Protection Department, Animal       is constrained. The influence of women is
            Production and Health Division.                              strong in the use of eggs, milk and poultry
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                                                                                                                                    15
meat for home consumption and they                   out of business. This is particularly evident
often have control over marketing these              for pig and poultry owners (Rola et al., 2006)
products and the income derived from                 but is not confined to those species. Given
them. Perhaps for this reason, poultry and           the more limited ability of women to start
small-scale dairy projects have been popular         their own businesses, this implies that they
investments for development projects that            will tend to become employees rather than
aim to improve the lot of rural women. In            self-employed. In specialized activities such
some countries, small-scale pig production is        as the production of day-old chicks, and in
also dominated by women. Female-headed               slaughtering, processing and retail, women
households are as successful as male-headed          are visible wherever painstaking semi-skilled
households in generating income from their           work is to be done, but very little research
animals, although they tend to own smaller           data are available about the extent of their
numbers of animals, probably because of              involvement compared with that of men, or
labour constraints. Livestock ownership is           their control over resources.
particularly attractive to women in societies
where access to land is restricted to men            Women in fisheries and aquaculture6
(Bravo-Baumann, 2000).                               In 2008, nearly 45 million people worldwide
   While the role of women in small-scale            were directly engaged, full time or part time,
livestock production is well recognized, much        in the fishery primary sector.7 In addition, an
less has been documented about women’s               estimated 135 million people are employed
engagement in intensive production and               in the secondary sector, including post-
the market chains associated with large              harvest activities. While comprehensive data
commercial enterprises. Demand for livestock         are not available on a sex-disaggregated
products, fuelled by rising incomes, has             basis, case studies suggest that women
grown much faster than the demand for crop           may comprise up to 30 percent of the total
staples during the past 40 years – particularly      employment in fisheries, including primary
in Asia and Latin America – and this trend is        and secondary activities.
expected to continue. While pastoralist and             Information provided to FAO from 86
small-scale mixed-farming systems continue           countries indicates that in 2008, 5.4 million
to be important in meeting the needs of              women worked as fishers and fish farmers
rural consumers, the demands of growing              in the primary sector. This represents
urban populations are increasingly supplied          12 percent of the total. In two major
with meat, milk and eggs from intensive              producing countries, China and India,
commercial systems. This has implications            women represented a share of 21 percent
for the engagement of women in the                   and 24 percent, respectively, of all fishers and
livestock sector because of the different            fish farmers.
roles, responsibilities and access to resources         Women have rarely engaged in commercial
that are evident within different scales of          offshore and long-distance capture
production system and at different points on         fisheries because of the vigorous work
the production and marketing chain.                  involved but also because of their domestic
   The available evidence suggests that the          responsibilities and/or social norms. They
role of women in meeting these changing              are more commonly occupied in subsistence
demands may diminish, for two reasons.               and commercial fishing from small boats and
The first is that when livestock enterprises         canoes in coastal or inland waters. Women
scale up, the control over decisions and             also contribute as entrepreneurs and provide
income, and sometimes the entire enterprise,         labour before, during and after the catch
often shifts to men. This is not a universal         in both artisanal and commercial fisheries.
phenomenon – in Viet Nam, for example,               For example, in West Africa, the so called
many medium-sized duck-breeding                      “Fish Mamas” play a major role: they usually
enterprises are managed by women – but it
is common and can be explained by women’s            6	
                                                        The material in this section was prepared by FAO’s
limited access to land and credit. The second        Fisheries and Aquaculture Department.
                                                     7	
                                                        FAO’s Fisheries and Aquaculture Department regularly
important factor is that all smallholders
                                                     collects employment statistics in fisheries and aquaculture
face challenges when the livestock sector            related to the primary sector only. The data therefore
intensifies and concentrates and many go             exclude post-harvest activities.
16   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




            own capital and are directly and vigorously                  IFAD, 2009). Studies conducted by FAO in
            involved in the coordination of the fisheries                Africa and Europe indicate that women do
            chain, from production to the sale of fish.                  not hold senior or policy-making positions
               Studies of women in aquaculture,                          in the sector. Rather, they are primarily
            especially in Asia where aquaculture                         employed in administrative and support
            has a long tradition, indicate that the                      roles, with professional women foresters
            contribution of women in labour is often                     tending to have specialist roles (e.g. research)
            greater than men’s, although macro-level                     or first-line junior management positions.
            sex-disaggregated data on this topic is                      There is limited information on the numbers
            almost non-existent. Women are reported                      and roles of women in contracting or self-
            to constitute 33 percent of the rural                        employed forestry work (FAO, 2006a, 2007).
            aquaculture workforce in China, 42 percent                   The studies indicate that even though women
            in Indonesia and 80 percent in Viet Nam                      are still underrepresented in the industry,
            (Kusabe and Kelker, 2001).                                   examples of good practice are emerging,
               The most significant role played by women                 especially in Europe (FAO, 2006a). This shows
            in both artisanal and industrial fisheries is                that concerted and sustained commitment
            at the processing and marketing stages,                      and planning at senior organizational levels
            where they are very active in all regions.                   can result in quantifiable improvements in
            In some countries, women have become                         the number of professional women foresters
            significant entrepreneurs in fish processing;                employed and the level of seniority they can
            in fact, most fish processing is performed by                attain.
            women, either in their own household-level
            industries or as wage labourers in the large-
            scale processing industry.                                   Women in rural labour markets

            Women in forestry                                            About 70 percent of men and 40 percent
            Women contribute to both the formal and                      of women in developing countries are
            informal forestry sectors in many significant                employed (Figure 4A). Male employment
            ways. They play roles in agroforestry,                       rates range from more than 60 percent in
            watershed management, tree improvement,                      the Near East and North Africa to almost
            and forest protection and conservation.                      80 percent in sub-Saharan African. Female
            Forests also often represent an important                    employment rates vary more widely across
            source of employment for women, especially                   regions, from about 15 percent in the Near
            in rural areas. From nurseries to plantations,               East and North Africa to over 60 percent in
            and from logging to wood processing,                         sub-Saharan Africa.
            women make up a notable proportion of the                      In Asia and in sub-Saharan Africa, women
            labour force in forest industries throughout                 who are employed are more likely to be
            the world. However, although women                           employed in agriculture than in other
            contribute substantially to the forestry                     sectors (Figure 4B). Almost 70 percent of
            sector, their roles are not fully recognized                 employed women in Southern Asia and
            and documented, their wages are not                          more than 60 percent of employed women
            equal to those of men and their working                      in sub-Saharan Africa work in agriculture.
            conditions tend to be poor (World Bank, FAO                  Furthermore, in most developing country
            and IFAD, 2009).                                             regions, women who are employed are just
              The Global Forest Resources Assessment                     as likely, or even more likely, than men to
            2010 reports that the forestry sector                        be in agriculture. The major exception is
            worldwide employed approximately                             Latin America, where agriculture provides a
            11 million people in 2005; however, sex-                     relatively small source of female employment
            disaggregated data on the number of                          and women are less likely than men to work
            women employed by the sector are not                         in the sector.
            available on a comprehensive basis (FAO,                       In most developing countries, a relatively
            2010c). Evidence from developing countries                   small share of the population works for a
            suggests that women are often employed in                    wage, and women are less likely to do so
            menial jobs in sawmills, plantation nurseries                than men (World Bank, 2007a). For rural
            and logging camps (World Bank, FAO and                       areas, data collected by the Rural Income
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                                                                                                                                                 17
      FIGURE 4
      Employment by sector


      A - Employed population as a share of total adult population, by sex and sector
      Percentage of total male
      and female population, respectively
      80
      70
      60
      50
      40
      30
      20
      10
       0
            Males Females Males Females Males Females Males Females Males Females Males Females
             Developing    Eastern and  Latin America Near East and Southern Asia Sub-Saharan
              countries   Southeastern     and the    North Africa                   Africa
                               Asia       Caribbean


      B - Distribution of male and female employment, by sector
      Percentage of male
      and female employment, respectively
     100
       90
       80
       70
       60
       50
       40
       30
       20
       10
        0
            Males Females Males Females Males Females Males Females Males Females Males Females
             Developing    Eastern and  Latin America Near East and Southern Asia Sub-Saharan
              countries   Southeastern     and the    North Africa                   Africa
                               Asia       Caribbean



                                   Agriculture                     Industry                      Services

Note: The data cover only a subset of the countries in each region. Definitions of adult labour force differ by country,
but usually refer to the population aged 15 and above.
Source: ILO, 2009.


Generating Activities (RIGA) project show                          For example, almost 15 percent of men
that the gender gap in formal and informal                         but fewer than 4 percent of women are
wage employment is large (Figure 5).8                              employed for wages in Ghana. The gap is
                                                                   even wider in some other countries, such as
8	
   Rural Income Generating Activities (RIGA) is a FAO project      Bangladesh, where 24 percent of rural men
that has created an internationally comparable database of         and only 3 percent of rural women work in
rural household income sources from existing household living      wage employment. A similar pattern holds in
standards surveys for more than 27 countries (FAO, 2010d).
                                                                   Latin America also; for example, in Ecuador
Most of the surveys used by the RIGA project were developed
by national statistical offices in conjunction the World Bank as   almost 30 percent of rural men and only
part of its Living Standards Measurement Study (LSMS).             9 percent of rural women receive a wage.
18   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                   FIGURE 5
                   Participation in rural wage employment, by gender


                     Ecuador
                  Guatemala
                   Nicaragua
                      Panama


                 Bangladesh
                    Indonesia
                        Nepal
                    Tajikistan
                    Viet Nam


                       Ghana
                      Malawi
                       Nigeria

                                 0              5             10         15           20          25         30         35

                                                      Percentage of adult population working for a wage


                                                             Women                      Men

            Source: FAO, 2010d.


               Even when rural women are in wage                                Differences in male and female
            employment, they are more likely to be                            employment and wage patterns may have
            in part-time, seasonal and/or low-paying                          multiple causes. Because women in many
            jobs. In Malawi, for example, 90 percent of                       countries have less education and work
            women and 66 percent of men work part-                            experience than men, they may earn a lower
            time (Figure 6A). In Nepal, 70 percent of                         wage. Furthermore, having less education
            women and 45 percent of men work part-                            and experience reduces their bargaining
            time. This pattern is less pronounced in Latin                    power so they may be more likely to accept
            America than in other regions.                                    low wages and irregular working conditions
               Rural wage employment is characterized                         (Kantor, 2008). Evidence from a number of
            by a high prevalence of seasonal jobs                             studies confirms that women, on average,
            for both men and women, but in most                               are paid less than men even for equivalent
            countries women are more likely than men                          jobs and comparable levels of education
            to be employed seasonally (Figure 6B). For                        and experience (Ahmed and Maitra, 2010;
            example, in Ecuador, almost 50 percent of                         Fontana, 2009). At the same time, because
            women but fewer than 40 percent of men                            women face significant time constraints
            hold seasonal jobs.                                               because of family obligations, they may prefer
               Similarly, rural wage-earning women are                        part-time or seasonal jobs that are typically
            more likely than men to hold low-wage jobs                        lower paid. Social norms that confine women
            (Figure 6C), defined as paying less than the                      to certain sectors or phases of the supply
            median agricultural wage. In Malawi, more                         chain can further limit their opportunities for
            than 60 percent of women are in low-wage                          career growth and reinforce these sectors as
            jobs compared with fewer than 40 percent                          low-pay and low-status occupations.
            of men. The gap is even wider in Bangladesh,                        Average male wages are higher than
            where 80 percent of women and 40 percent of                       average female wages in rural and urban
            men have low-wage jobs. The only exception                        areas of the countries covered by the
            to this pattern was found in Panama.                              RIGA dataset (Figure 7). For example, in
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                                                                                                                                            19
     FIGURE 6
     Conditions of employment in rural wage employment, by gender

     A - Prevalence of part-time work

        Ecuador
     Guatemala
      Nicaragua
        Panama

     Bangladesh
       Indonesia
           Nepal
       Tajikistan
        Viet Nam

         Ghana
         Malawi
         Nigeria
                    0      10        20          30     40        50        60        70        80        90       100
                                                             Percentage

     B - Prevalence of seasonal work1

        Ecuador
     Guatemala
      Nicaragua
        Panama

     Bangladesh
       Indonesia
           Nepal
       Tajikistan
        Viet Nam

         Malawi
                    0      10        20          30     40        50        60        70        80        90       100
                                                             Percentage

     C - Prevalence of low-wage work

        Ecuador
     Guatemala
      Nicaragua
        Panama

    Bangladesh
      Indonesia
          Nepal
      Tajikistan
       Viet Nam

         Ghana
         Malawi
         Nigeria

                    0      10        20          30     40        50        60        70        80        90       100
                                                             Percentage


                                           Women                            Men

1
 Data are not available for Ghana and Nigeria.
Source: FAO, 2010d.
20   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




             Ghana, men’s wages are 31 percent higher                     developments for female employment over
             than women’s wages in urban areas and                        the past few decades (Deere, 2005).
             58 percent higher in rural areas. Women earn                   Women are clearly an important part
             less than men everywhere except in rural                     of the agricultural labour force, but
             areas of Panama. The gap between male and                    agriculture and agricultural value chains
             female wages is wider in rural areas in some                 are equally important to women as a
             countries, but not everywhere. Women in                      source of employment. Commercial value
             most RIGA countries typically earn less than                 chains for high-value products such as fresh
             men with the same qualifications, partly as                  fruit, vegetables, flowers and livestock
             a consequence of occupational segregation                    products are growing rapidly to supply
             and discrimination (Hertz et al., 2009).                     urban supermarkets and export markets.
               While women continue to face                               The growth of modern value chains and
             occupational segregation and discrimination                  the broader structural transformation of
             in rural labour markets, new forms of                        the agriculture sector in many developing
             organization in supply chains for export-                    countries have major implications for
             oriented crops and agroprocessing have                       women’s employment, but the impact
             created better-paying employment                             of these trends for women has received
             opportunities for women than had existed                     relatively little analytical attention (Maertens
             before. Wages are typically higher and                       and Swinnen, 2009).
             working conditions better than in traditional                  Women dominate employment in many
             agricultural employment. The large-scale                     of the high-value agricultural commodity
             incorporation of women in the packing stage                  chains in Africa and Latin America (Table 1).
             of non-traditional agro-export production                    Although new jobs in export-oriented agro-
             may be one of the most important                             industries may not employ men and women


                   FIGURE 7
                   Wage gap between men and women in urban and rural areas



                    Ecuador
                 Guatemala
                  Nicaragua
                     Panama


                Bangladesh
                  Indonesia
                       Nepal
                   Tajikistan
                   Viet Nam


                      Ghana
                     Malawi
                     Nigeria

                              -20         -10           0         10     20      30       40         50        60         70

                                                                         Percentage



                                                             Rural                    Urban

             Note: The wage gap is calculated as the difference between average daily male and female wages as a percentage of
             the average male wage. A positive wage gap means men are paid more than women. The rural wage gap includes farm
             and non-farm employment.
             Source: Hertz et al. 2009.
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                                                                                                                                             21
 TABLE 1
 Employment in selected high-value agro-industries
                                                       Year of         Number of employees            Share of female
         Country                Commodity
                                                       survey          in the agro-industry            employees (%)

 Cameroon                  Banana                        2003                     10 000                        ..


 Côte d’lvoire             Banana and pineapple          2002                     35 000                        ..


 Kenya                     Flowers                       2002             40 000–70 000                        75

                           French beans                  2005                     12 000                       90
 Senegal                   Cherry tomatoes               2006                      3 000                       60

 Uganda                    Flowers                       1998                      3 300                       75


 South Africa              Deciduous fruit               1994                    283 000                       53

                           Vegetables                   2002/3                     7 500                       65
 Zambia                    Flowers                      2002/3                     2 500                       35

 Chile                     Fruits                        1990s                   300 000                  circa 46


 Colombia                  Flowers                      mid-90s                   75 000                    60–80

                           Fruits, vegetables,
 Dominican Republic        flowers, plants
                                                        1989–90                   16 955                  circa 41


 Mexico                    Vegetables                    1990s                   950 000                       90

Sources: For Africa: Maertens and Swinnen, 2009, Table 1, based on several sources; for South America: Deere, 2005,
Appendix II, based on several sources.


on equal terms, they often provide better                       in some surprising ways (Newman, 2002). The
opportunities for women than exist within                       total time spent by women in paid and unpaid
the confines of traditional agriculture and                     work did not increase, contrary to a frequent
can also be instruments of change with                          criticism of agricultural export development
positive implications for women and rural                       that maintains that women are unduly
development (Maertens and Swinnen, 2009;                        burdened by work in the industry. Indeed, the
Deere, 2005).                                                   most compelling evidence of the industry’s
   The flower industry in Latin America                         impact was on men’s increased participation in
provides an interesting case of contrasting                     housework. In Cotocachi, Ecuador, in contrast,
points of view. In Colombia, for example,                       women were not prepared to move or even
Friedemann-Sanchez (2006) finds that                            commute to work in the flower industry
64 percent of the workforce directly growing                    despite the higher wages offered there.
fresh-cut flowers for export are women and                      The women did not view flower industry
considers this type of agro-industrial work                     employment as an option, indicating either
skilled, while others consider it unskilled                     that their husbands would not allow them to
(e.g. Meier, 1999). While women do have                         work or that the work would be detrimental
supervisory jobs among those directly                           to family relations (Newman, 2002).
involved in cultivation activities, they                           In Senegal, the growth of modern
have a much lower share of managerial or                        horticulture supply chains has been
professional jobs in other aspects of the                       associated with direct beneficial effects
sector (Friedemann-Sanchez, 2006). Similarly,                   for rural women and reduced gender
Fontana (2003) finds that in sectors producing                  inequalities in rural areas (Maertens and
primarily for the export market, women tend                     Swinnen, 2009). The study also finds that
to be replaced by males as profits increase.                    women benefit more from employment
   The arrival of the flower industry in the                    in large-scale estate production and agro-
Ecuadorian town of Cayambe in the late 1980s                    industrial processing than from high-value
(in combination with other household and                        smallholder contract-farming in which they
individual factors) affected time-use patterns                  often provide unpaid family labour.
22   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                                                                         •	 Agriculture is the most important source
             Key messages                                                   of employment for women in rural areas
                                                                            in most developing country regions, but
                •	 Women comprise 43 percent of the                         this varies widely by region. Women are
                   agricultural labour force in developing                  more likely than men to hold low-wage,
                   countries, on average, ranging from                      part-time, seasonal employment and
                   about 20 percent in Latin America                        they tend to be paid less even when their
                   to almost 50 percent in Eastern and                      qualifications are higher than men’s, but
                   Southeastern Asia and sub-Saharan                        new jobs in high-value, export-oriented
                   Africa. The share is higher in some                      agro-industries offer much better
                   countries and is changing rapidly in some                opportunities for women than traditional
                   parts of the world.                                      agricultural work.
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                                                                                                                                    23
3. 	Documenting the gender gap
    in agriculture9


Access to productive resources such as land,         less likely to own or operate land; they are
modern inputs, technology, education and             less likely to have access to rented land, and
financial services is a critical determinant         the land they do have access to is often of
of agricultural productivity. Agriculture            poorer quality and in smaller plots.
is important to women, but female                       The most comprehensive data on women’s
farmers (Box 4) have less access to the              access to land come from the FAO Gender
productive resources and services required           and Land Rights Database (FAO, 2010f), and
by agricultural producers. Women are less            were collected from different data sources,
likely than men to own land or livestock,            including household surveys, agricultural
adopt new technologies, use credit or other          censuses and the academic literature. The
financial services, or receive education or          database provides information on the shares
extension advice. In some cases, women do            of “agricultural holders” who are male and
not even control the use of their own time.          female. An agricultural holder is defined as
   While the size of the gender gap differs          the person or group of persons who exercise
by resource and location, the underlying             management control over an agricultural
causes for the gender asset gap are repeated         holding. The holding may be owned,
across regions: social norms systematically          rented or allocated from common property
limit the options available to women.                resources and may be operated on a share-
Regardless of cause or magnitude, however,           cropped basis.
the gender asset gap reduces the agricultural           Stark gender disparities in land holdings
productivity of women and thus involves              are apparent in all regions (Figure 8).
broader economic and social costs.                   Women represent fewer than 5 percent
                                                     of all agricultural holders in the countries
                                                     in North Africa and West Asia for which
Land                                                 data are available. The sub-Saharan African
                                                     average of 15 percent masks wide variations,
Land is the most important household asset           from fewer than 5 percent in Mali to over
for households that depend on agriculture            30 percent in countries such as Botswana,
for their livelihoods. Access to land is a basic     Cape Verde and Malawi. Latin America
requirement for farming and control over             has the highest regional average share of
land is synonymous with wealth, status               female agricultural holders, which exceeds
and power in many areas. Strengthening               25 percent in Chile, Ecuador and Panama.
women’s access to, and control over, land               In addition to being more likely to hold
is an important means of raising their               land, men also typically control larger land
status and influence within households and           holdings than women. Representative and
communities. Improving women’s access                comparable data for 20 countries from the
to land and security of tenure has direct            RIGA database of household surveys show
impacts on farm productivity, and can also           that male-headed households operate larger
have far-reaching implications for improving         agricultural land holdings, on average, than
household welfare. Strengthening land                female-headed households in all countries
ownership by women in Nepal, for example,            (Figure 9). Inequality in access to land is more
is linked with better health outcomes for            acute in Bangladesh, Ecuador and Pakistan,
children (Allendorf, 2007).                          where average land holdings of male-headed
   The evidence illustrating gender inequalities     households are more than twice the size of
in access to land is overwhelming. Women
across all developing regions are consistently       9	
                                                          The material in this chapter is based on FAO (2010e).
24   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                BOX 4
                Female farmers, household heads and data limitations


                Data on female farmers are limited. Most                    A distinction should be made between
                women engaged in farming do so within                    two types of female-headed households:
                a household production unit, and their                   (i) de facto, i.e. those in which an adult
                activities are not usually separable from                male partner is working away from the
                those of the household as a whole. Most of               household but remains involved through
                the data available on female farmers derives             remittances and other economic and
                from household surveys and pertains to the               social ties and (ii) de jure, i.e. those which
                activities of female-headed households, who              have no male partner, such as women
                comprise a minority of female farmers in                 who are widowed, divorced or never
                most countries. Some data are available for              married. Comprehensive data are not
                female-operated plots within male-headed                 usually available to distinguish between
                households, primarily in Africa where men                these types of households, but for the
                and women often operate separate plots.                  few cases for which we have data most
                The unit of observation used in this chapter             female-headed households are de jure.
                (individuals, households, farms or plots)                In Malawi, Panama and Uganda about
                varies depending on the resource being                   70, 63 and 83 percent, respectively, of
                discussed and the availability of data.                  all female-headed households are de
                   The prevalence of female-headed                       jure (Chipande, 1987; Appleton, 1996;
                households is generally higher in sub-                   and Fuwa, 2000). Also in Cambodia and
                Saharan Africa than in other regions                     the Lao People’s Democratic Republic,
                (Annex table A5), but this hides                         most are de jure (FAO/GSO/MoP, 2010,
                considerable variation within the region.                and FAO/MAF, 2010). Studies that are
                In fact, the countries having the highest                able to disaggregate by type of female-
                (Swaziland) and the lowest (Burkina Faso)                headed household mostly find that de
                prevalence of female-headed households                   jure households are more likely to suffer
                in developing regions are both found in                  from a range of economic and social
                sub-Saharan Africa.                                      disadvantages (Seebens, 2010).



             those of female-headed households. The                      to systematic gender inequalities. Male-
             RIGA results confirm the findings of studies                headed households have larger livestock
             in Latin America (Deere and León, 2003)                     holdings, on average, than female-headed
             and Africa (FAO, 1997) showing that male-                   households (Figure 10). Inequality in livestock
             controlled land holdings are generally larger               holdings appears to be particularly acute in
             than female-controlled holdings.                            Bangladesh, Ghana and Nigeria, where male
                                                                         holdings are more than three times larger
                                                                         than those of female-headed households. In
             Livestock                                                   Indonesia and Pakistan, for which the RIGA
                                                                         database contains information on incomes
             Livestock is another key asset in rural areas               from livestock but not livestock holdings,
             (FAO, 2009a). In many countries, livestock                  net incomes from livestock are significantly
             is one of the most valuable agricultural                    higher in male-headed households than in
             assets and represents a source of income                    female-headed households.
             and wealth accumulation as well as an                          The RIGA database provides information
             important source of resistance to shocks.                   by household according to the sex of the
             Draught animals are also the main source                    household head, so data do not reflect
             of power for ploughing, land clearing and                   intra-household differences in control over
             transportation in many regions.                             livestock. These vary by culture and context
                As was the case for access to land, the                  but, in general, men are responsible for
             evidence for livestock holdings points                      keeping and marketing large animals, such
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                                                                                                                                                 25
      FIGURE 8
      Share of male and female agricultural holders in main developing regions



     Latin America and the Caribbean


                       Sub-Saharan Africa


  Southern Asia and Southeastern Asia


            North Africa and West Asia


                                  Oceania

                                             0       10       20       30   40      50     60       70       80    90   100
                                                                                 Percentage



                                             Female                                Male

Note: Regional aggregates do not include all countries due to lack of data. Country-level data are provided in Annex table A5.
Source: FAO, 2010f.



     FIGURE 9
     Rural household assets: farm size


         Bolivia
       Ecuador
    Guatemala
     Nicaragua
        Panama


   Bangladesh
      Indonesia
          Nepal
       Pakistan
      Tajikistan
      Viet Nam


         Ghana
   Madagascar
        Malawi

                   0       1        2         3           4        5        6        7          8        9        10     11
                                                          Average farm size (ha)



                               Female-headed households                             Male-headed households

Note: Differences between male and female-headed households are statistically significant at the 95 percent confidence
level for all countries, except for Bolivia, Indonesia, Madagascar, Nicaragua and Tajikistan.
Sources: FAO, 2010d, and Anríquez, 2010.
26   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                   FIGURE 10
                   Household livestock assets, in male- and female-headed households



                      Bolivia
                     Ecuador
                 Guatemala
                  Nicaragua
                     Panama


                Bangladesh
                        Nepal


                       Ghana
                Madagascar
                      Malawi
                      Nigeria

                                0.0     0.5        1.0      1.5          2.0   2.5    3.0      3.5       4.0      4.5      5.0      5.5

                                                                Average tropical livestock unit (TLU)


                                              Female-headed households                         Male-headed households

             Notes: Calculations made using nationally representative household surveys. The number of livestock is computed using
             the tropical livestock unit (TLU), which is equivalent to a 250 kg animal. The scale varies by region. For example, in South
             America, the scale is: 1 bovine = 0.7 TLU, 1 pig = 0.2, 1 sheep = 0.1 and 1 chicken = 0.01. Differences between male- and
             female-headed households are statistically significant at the 95 percent confidence level for all countries except for
             Guatemala.
             Sources: FAO, RIGA team, and Anríquez, 2010.


             as cattle, horses and camels, while women                          the form of large animals such as cows and
             tend to control smaller animals, such as                           bulls while women are more likely to hold
             goats, sheep, pigs and poultry (FAO, 2009a).                       assets in the form of small animals, household
             In Nicaragua, for example, women own                               durable goods and jewellery. Women tend
             around 10 percent of work animals and                              to draw down assets more quickly than men
             cattle but 55–65 percent of pigs and poultry                       in response to crises and as they get older
             (Deere, Alvarado and Twyman, 2009). Even                           (Dillon and Quiñones, 2010).
             when women jointly own large animals, they
             do not necessarily have access to the services
             they provide, as was found for Indian women                        Farm labour
             and the use of oxen (Chen, 2000).
                The RIGA data measure livestock in physical                     Labour availability depends on the amount
             terms – tropical livestock units – but the                         of family labour that a household can
             results are consistent with other studies that                     mobilize and the amount of labour that can
             evaluate the value of livestock holdings. Data                     be hired in local labour markets. Labour
             from northern Nigeria, for example, indicate                       constraints can be more acute for both
             that the value of men’s livestock holdings                         women and female-headed households
             is about twice that of women’s (Dillon and                         than for men and male-headed households
             Quiñones, 2010). The same study finds that                         for several reasons. Women generally face
             men and women use livestock differently                            gender-specific constraints as agricultural
             as a store of wealth and as a buffer against                       labourers and in hiring-in labour. Low levels
             shocks. Men are more likely to hold assets in                      of human capital – education, health and
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                                                                                                                                   27
nutrition – are a constraint on women’s             that female-headed households typically
labour productivity in agriculture and other        farm smaller plots may not compensate for
sectors (Behrman, Alderman and Hoddinott,           the lower availability of family labour. For
2004) (Box 5). Some nutrition issues, such          example, among small-scale maize farmers
as iron deficiency, which directly affects          in Malawi, females own less land but still
labour productivity and is widespread, are          use about 10 percent less total labour per
especially relevant to women (Quisumbing            hectare than their male counterparts and
and Pandolfelli, 2010). Often there is a            much of that labour is supplied by children,
pronounced gender division of labour for            who must work to make up the shortfall
particular agricultural tasks, with the result      caused by their mothers’ other duties
that male and female labour cannot be easily        (Takane, 2008).
substituted. Moreover, women are time-                Household and community responsibilities
constrained by domestic tasks such as care-         and gender-specific labour requirements
giving and collecting firewood and water            mean that women farmers cannot farm
(McGuire and Popkin, 1970; Quisumbing and           as productively as men and make it more
Pandolfelli, 2010).                                 difficult for them to respond when crop
  Female-headed households face more                prices rise. Depending on cultural norms,
severe labour constraints than male-headed          some farming activities, such as ploughing
households because they typically have              and spraying, rely on access to male labour
fewer members but more dependants. In               without which women farmers face delays
some areas, male out-migration adds to              that may lead to losses in output. For
the constraint already imposed by gender-           example, women maize farmers in Malawi
specific farming tasks (Peters, 1986). Female-      require male labour for ploughing, but
headed households may receive help from             female-headed households often lack male
male relatives, but only after the men have         family members who can do the work and
taken care of their own plots. The fact             they may not have the cash needed to hire


  BOX 5
  Labour productivity and hunger, nutrition and health


  Hunger, nutrition and health are strong            whereas the opposite is true in sub-
  determining factors on a person’s ability          Saharan Africa.
  to work, their productivity and their                 While in some locations women are
  cognitive development. With regard to              disadvantaged with regard to hunger and
  nutrition, only 37 developing countries            nutrition, this is not generally the case.
  collect data on chronic energy deficiency          However, there are certain health and
  (CED) for both men and women (Annex                nutritional issues that are sex-specific. For
  table A6) (WHO, 2010). In 17 countries the         example, women’s energy and nutritional
  difference between the share of men and            needs increase during menstruation,
  women with CED is one or less percentage           pregnancy and lactation and their
  points. Of the remaining 20 countries,             nutritional status has an impact on their
  13 show a higher share of women with               offspring. There is also evidence that women
  CED. Based on these few observations,              have higher morbidity than men – not only
  it appears that in sub-Saharan Africa              because they live longer – and that they are
  women are less likely than men to suffer           less likely to access health services (Buvinic
  CED while in South America and Asia,               et al., 2006). Thus, gender differences in
  particularly Southeastern Asia, women are          nutrition and health could have important
  more likely than men to suffer from CED.           policy implications for society.
  The reported data for adults are consistent           Policy interventions that address the
  with that available for underweight                specific health and nutrition issues of
  children (under 5 years of age). For               women are important, but their nature
  example, in Asia and the Pacific, a larger         and scope should always reflect the
  share of girls than boys are underweight,          specific context and location.
28   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




             male labour. As a result, women cultivate                       The level of human capital available in
             smaller plots and achieve lower yields                          a household (usually measured as the
             (Gilbert, Sakala and Benson, 2002). This web                    education of the head of household or the
             of constraints means that women in Malawi                       average education of working-age adults in
             have difficulty growing cash crops such as                      the household) is strongly correlated with
             tobacco or improved maize that require                          measures such as agricultural productivity,
             purchased inputs, because they cannot                           household income and nutritional outcomes
             generate the income necessary to obtain                         – all of which ultimately affect household
             credit and guarantee repayment. Such labour                     welfare and economic growth at the national
             constraints in some cases may prevent female-                   level (World Bank, 2007a).
             headed households from even applying for                           Gender differences in education are
             credit (Chipande, 1987). Female-headed                          significant and widespread (Figure 11).
             households in Ethiopia, where cultural norms                    Female heads have less education than
             require that ploughing be undertaken by                         their male counterparts in all countries
             men, also achieve lower yields because they                     in the sample except Panama, where the
             have limited access to male labour (Holden,                     difference is not statistically significant. The
             Shiferaw and Pender, 2001).                                     data suggest that female household heads in
                                                                             rural areas are disadvantaged with respect
                                                                             to human capital accumulation in most
             Education                                                       developing countries, regardless of region or
                                                                             level of economic development.
             Human capital is a major factor in                                 This evidence reflects a history of bias
             determining the opportunities available to                      against girls in education. Despite this bias,
             individuals in society and is closely linked                    human capital accumulation is one asset
             to the productive capacity of households                        category for which the gender gap has
             and their economic and social well-being.                       clearly narrowed in recent decades. Although


                   FIGURE 11
                   Education of male and female rural household heads


                     Bolivia
                    Ecuador
                 Guatemala
                  Nicaragua
                    Panama


                Bangladesh
                 Indonesia
                      Nepal
                   Pakistan
                  Tajikistan
                  Viet Nam


                   Ghana
               Madagascar
                  Malawi
                  Nigeria

                                0         1         2         3          4   5      6      7      8       9     10     11

                                                         Average years of education of household head


                                              Female-headed households                    Male-headed households

             Sources: FAO, 2010d, and Anríquez, 2010.
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     FIGURE 12
     Gender differences in rural primary education attendance rates


         Ecuador
     Guatemala
      Nicaragua
         Panama


     Bangladesh
       Indonesia
           Nepal
        Pakistan
       Viet Nam


          Ghana
    Madagascar
         Malawi
          Nigeria

                    0       10        20       30       40        50        60        70       80        90       100

                                           Net primary attendance rates (percentage)



                                               Female                       Male

Note: Attendance rates are defined as the number of children in primary school age who attend primary school, expressed
as a percentage of the total number of children in official primary school age. Only Ghana, Guatemala, Nepal and Pakistan
are statistically significantly different from 0 at the 95 percent level.
Source: FAO, RIGA team.


progress has been uneven across regions                       science and technology is particularly
and important gaps persist, significant gains                 relevant in regions where women comprise
have been made in primary school enrolment                    a large part of the agriculture sector. The
rates for girls, and difference between boys                  number of women working in science
and girls has narrowed. Of the 106 countries                  and technology research in industrialized
committed to MDG 3 on gender parity in                        and developing countries has increased
access to education, 83 had met the target                    substantially in recent decades, but remains
by 2005 (World Bank, 2007b). Most of the                      low in most countries. There is an urgent
countries in the RIGA database have achieved                  need for a greater representation of women
gender parity in primary school attendance                    in agricultural research, particularly in sub-
(defined as no statistically significant                      Saharan Africa, where women participate
difference between male and female                            heavily in the agricultural workforce. Women
attendance rates) (Figure 12). One of the                     scientists, research managers, lecturers and
most significant advances for women in Latin                  professors can provide different insights
America has been in the area of primary                       and perspectives and help research agencies
and secondary education, yet a significant                    to address more effectively the unique and
gender gap persists among indigenous                          pressing challenges that African farmers
groups in many Latin American countries.                      face. They may also serve as role models to
The education gender gap – both in levels of                  students and other women in agriculture.
enrolment and attainment – remains widest                     Significant progress has been made in
in Southern Asia and sub-Saharan Africa.                      increasing the share of female professional
  Beyond general educational attainment,                      staff in agricultural higher education and
higher education for women in agricultural                    research institutions in Africa (Box 6).
30   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                 BOX 6
                 Women in agricultural higher education and research in Africa1


                 During 2008, the Agricultural Science                         the Niger (10 percent) and Burkina Faso
                 and Technology Indicators (ASTI) and the                      (12 percent). Compared with other
                 African Woman in Agricultural Research                        countries in the region, female professional
                 and Development (AWARD) programmes                            staff members were relatively more
                 conducted a survey to obtain sex-                             educated in Kenya, Nigeria, South Africa
                 disaggregated capacity indicators covering                    and Uganda, where more than one-quarter
                 125 agricultural research and higher                          of the total held PhD degrees.
                 education agencies in 15 sub-Saharan                            Future trends in female participation in
                 African countries.2 The study found that the                  agricultural research will be influenced by
                 pool of female professional staff increased                   current student enrolment and graduation
                 by 50 percent between 2000/01 and                             levels. An increasing number of women
                 2007/08 and 4 (Botswana, Nigeria, Senegal,                    have been enrolling in higher education,
                 and Zambia) of the 15 countries saw their                     not only in sub-Saharan Africa, but also
                 female staff double. In relative terms, the                   in other regions in the world (UIS, 2006;
                 share of women in total professional staff                    UNESCO, 2004). This also appears to
                 increased from 18 percent to 24 percent                       be the case in agricultural sciences, but
                 over the period. This increase occurred                       unfortunately no sex-disaggregated trend
                 across all three degree levels (BSc, MSc,                     data are available. Most female students
                 and PhD), but varied considerably across                      in agricultural sciences, however, are
                 the 15 countries (Figures A and B). Female                    enrolled in BSc programmes. This is also
                 participation in agricultural research and                    true for male students and reflects the
                 higher education was particularly high in                     reality that many agricultural faculties and
                 South Africa (41 percent), Mozambique                         schools in sub-Saharan Africa have only
                 (35 percent) and Botswana (32 percent).                       small MSc and PhD programmes.
                 In contrast, only a small proportion of the                     The growing shares of professional
                 agricultural professional staff were women                    women employed in agriculture and
                 in Ethiopia (6 percent), Togo (9 percent),                    female students enrolled in agricultural


                       FIGURE A
                       Change in average female shares in professional staff of agricultural and higher
                       education institutions in 14 African countries, by degree level, 2000/01 to 2007/08

                       Percentage
                       30

                       25

                       20

                       15

                       10

                         5

                         0
                                       BSc                        MSc                   PhD               Total

                                                                         Degree level


                                                                     2000/01                  2007/08

                 Note: Excludes Mozambique owing to lack of available data for 2000/01.
                 Source: Beintema and Di Marcantonio, 2009, based on ASTI datasets.
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     FIGURE B
     Change in female shares in professional staff, by headcount, 2000/01 to 2007/08

       Botswana
    Burkina Faso
         Burundi
         Ethiopia
           Ghana
           Kenya
          Malawi
    Mozambique
            Niger
          Nigeria
         Senegal
     South Africa
            Togo
         Uganda
          Zambia
        Total (15)
        Total (14)

                     0      5        10       15         20        25        30        35        40        45

                                                        Percentage



                                             2000/01                      2007/08

Note: Excludes Mozambique owing to lack of available data for 2000/01.
Source: Beintema and Di Marcantonio, 2009, based on ASTI datasets.


sciences indicate that the gender gap                   ladder. Only 14 percent of management
in African agricultural sciences may                    positions were held by women, which is
be narrowing, especially in southern                    considerably lower than the overall share
Africa. But the increase in the number of               of female professional staff employed
women, as well as men, that enter African               in agriculture. Women are, therefore,
agricultural research and higher education              less represented in high-level research,
are mostly young staff with lower level                 management and decision-making
of degrees and at the beginning of the                  positions compared with their male
career ladder. On average, more than                    colleagues.
half of the female professional staff in
the 15-country sample were younger                      1
                                                          This section was prepared by Nienke Beintema
than 41 years compared with 42 percent                  and is based on Agricultural Science and
                                                        Technology Indicators (ASTI) datasets (www.asti.
of the total male professional staff. On                cgiar.org), Beintema (2006), and Beintema and
average, 31 percent of total female staff               Di Marcantonio (2009). ASTI is managed by the
and 27 percent of total male staff held BSc             International Food Policy Research Institute (IFPRI);
                                                        AWARD is managed by the Consultative Group on
degrees. These 15-country averages, again,              International Agricultural Research (CGIAR) Gender
mask a wide variation across countries (see             and Diversity (G&D) Program.
Beintema and Di Marcantonio, 2009).                     2
                                                         Botswana, Burkina Faso, Burundi, Ethiopia,
                                                        Ghana, Kenya, Malawi, Mozambique, the Niger,
   The share of women disproportionately                Nigeria, Senegal, South Africa, Togo, Uganda and
declines on the higher rungs of the career              Zambia.
32   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                                                                         Mekonnen and Spurling, 1994). Extension
             Information and extension                                   service agents tend to approach male farmers
                                                                         more often than female farmers because
             Good and timely information on new                          of the general misperception that women
             technologies and techniques is essential                    do not farm and that extension advice will
             for farmers when deciding whether or not                    eventually “trickle down” from the male
             to adopt an innovation. Although private                    household head to all other household
             extension services are playing an increasing                members. Extension services are often
             role in some countries, such as Brazil, China               directed towards farmers who are more likely
             and India, public extension services remain                 to adopt modern innovations, for example
             the key source of information on new                        farmers with sufficient resources in well-
             technologies for farmers in most developing                 established areas. As discussed above, women
             countries. Extension services encompass the                 are less likely to access resources and may
             wide range of services provided by experts                  therefore be bypassed by extension service
             in the areas of agriculture, agribusiness,                  providers (Meinzen-Dick et al., 2010).
             health and others and are designed to                          Finally, the way in which extension services
             improve productivity and the overall well-                  are delivered can constrain women farmers
             being of rural populations. The provision of                in receiving information on innovations.
             agricultural extension can lead to significant              Women tend to have lower levels of
             yield increases. Yet, extension provision                   education than men, which may limit their
             in developing economies remains low for                     active participation in training that uses a
             both women and men, and women tend to                       lot of written material. Time constraints and
             make less use than men of extension services                cultural reservations may hinder women from
             (Meinzen-Dick et al., 2010). According                      participating in extension activities, such
             to a 1988–89 FAO survey of extension                        as field days, outside their village or within
             organizations covering 97 countries with sex-               mixed groups (Meinzen-Dick et al. 2010).
             disaggregated data (the most comprehensive                     Several new and participatory extension
             study available) only 5 percent of all                      approaches have been developed and
             extension resources were directed at women.                 tested in the past decade in an effort to
             Moreover, only 15 percent of the extension                  move away from a top-down model of
             personnel were female (FAO, 1993).                          extension service provision to more farmer-
               In social contexts where meetings between                 driven services. These approaches can target
             women and men from outside the family                       women effectively and increase their uptake
             nucleus are restricted, a lack of female                    of innovations (Davis et al., 2009) and will
             extension agents effectively bars women                     be discussed in Chapter 5. Participatory
             from participating. The preference for female               approaches that encourage communication
             extension agents varies by country and marital              between farmers and researchers can also
             status. In Ghana, for example, male and                     lead to positive feedback loops that allow
             female farmers in male-headed households                    researchers to adjust innovations to local
             have equal contact with extension agents but                needs.
             female farmers in female-headed households                     Modern information and communication
             have much less contact, although they are                   technologies (ICTs) such as radio, mobile
             willing to speak to agents of either sex (Doss              phones, computers and Internet services can
             and Morris, 2001). In the United Republic of                also play an important role in transferring
             Tanzania, on the other hand, many female                    information. ICTs offer opportunities for
             farmers prefer to talk to a female extension                accessing and sharing information faster,
             officer and, by 1997, one-third of extension                networking, the mobilization of resources
             officers were women, up from almost none 15                 and educational purposes. Mobile phone
             years prior (Due, Magayane and Temu, 1997).                 subscriptions in developing countries have
               However, even when women have access                      doubled since 2005. To date, 57 out of 100
             to extension services, the benefits may not be              inhabitants (up from 23 in 2005) in developing
             obvious. In Kenya, contact with the extension               countries have a mobile phone subscription
             agent contributed significantly and positively              (ITU, 2010). These technologies may be
             to output on male-managed plots, but not                    beneficial for rural women whose ability
             necessarily on female-managed plots (Saito,                 to travel to distant markets is restricted.
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                                                                                                                                               33
Rural women may face barriers in accessing                      costs associated with the innovations and
ICTs because of their limited education and                     investment necessary to enhance their
financial and time constraints. Locations that                  productivity, income and well-being.
are convenient and appropriate for women                          Evidence shows that credit markets are not
to visit can help improve women’s access (Best                  gender-neutral. Legal barriers and cultural
and Maier, 2007).                                               norms sometimes bar women from holding
                                                                bank accounts or entering into financial
                                                                contracts in their own right. Women generally
Financial services                                              have less control over the types of fixed assets
                                                                that are usually necessary as collateral for
Financial services such as savings, credit                      loans. Institutional discrimination by private
and insurance provide opportunities for                         and public lending institutions often either
improving agricultural output, food security                    ration women out of the market or grant
and economic vitality at the household,                         women loans that are smaller than those
community and national levels. Many studies                     granted to men for similar activities (Fletschner,
have shown that improving women’s direct                        2009; World Bank, FAO and IFAD, 2009).
access to financial resources leads to higher                     In seven out of nine countries in the RIGA
investments in human capital in the form of                     dataset, rural female-headed households
children’s health, nutrition and education.                     are less likely than male-headed households
  Producers who are unable to cover                             to use credit (Figure 13). In Madagascar,
their short-term expenses or who want                           for example, the share of female-headed
to purchase more productive but more                            households that use credit is 9 percentage
expensive technologies must rely on either                      points smaller than the share of male-headed
credit markets or other credit sources.                         households who do so. The cases of Ghana
Without access to credit, producers may                         and Panama are noteworthy in that no
be unable to bear the risks and up-front                        gender gap is apparent in the use of credit.


     FIGURE 13
     Credit use by female- and male-headed households in rural areas


        Ecuador
     Guatemala
        Panama


      Indonesia
           Nepal
       Viet Nam


          Ghana
    Madagascar
         Malawi

                   0          10          20            30          40           50          60          70          80

                                               Percentage of households using credit



                        Female-headed households                                 Male-headed households

Note: Calculations made using nationally representative household surveys. The gender gap is calculated as the difference
between the percentages of male- and female-headed households that use credit.
Sources: FAO, RIGA team, and Anríquez, 2010.
34   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                The gender gap in access to credit is also               households typically receive loans only from
             confirmed by other evidence. In Nigeria,                    credit cooperatives as opposed to the state
             for example, 14 percent of males but only                   banks or wholesalers. Her findings show that
             5 percent of females obtain formal credit,                  women are less likely to use credit than men
             while in Kenya the percentages are 14 and                   under equivalent socio-economic conditions
             4 for males and females, respectively (Saito,               and that they are not always able to rely on
             Mekonnen and Spurling, 1994). In Uganda,                    their husbands to help them overcome credit
             women entrepreneurs receive just 1 percent                  constraints. These constraints on women’s
             of available credit in rural areas (Dolan,                  access to capital have a measurable negative
             2004). Also in Uganda, nearly all female-                   impact on their production capabilities. For
             headed households reported a desire to                      example, in addition to the efficiency loss
             expand agricultural activities but lacked the               associated with the husband’s credit constraints,
             money to purchase land and inputs such as                   when women are unable to meet their credit
             seeds, fertilizer and pesticides, and/or to                 needs their households experience an additional
             hire-in labour. They cited the lack of access to            11 percent drop in efficiency (Fletschner, 2008).
             credit as one of the most prominent barriers
             to livelihood diversification (Ellis, Manuel
             and Blackden, 2006).                                        Technology
                In Bangladesh, women received about
             5 percent of loans disbursed by financial                   Access to new technology is crucial in
             institutions to rural areas in 1980 and only                maintaining and improving agricultural
             slightly more than 5 percent in 1990, despite               productivity. Gender gaps exist for a wide
             the emergence of special credit programmes                  range of agricultural technologies, including
             for women in Bangladesh during the                          machines and tools, improved plant varieties
             research period (Goetz and Gupta 1996).                     and animal breeds, fertilizers, pest control
             Further evidence from Bangladesh suggests                   measures and management techniques. A
             that even when programmes succeed in                        number of constraints, including the gender
             improving the access of women to credit,                    gaps described above, lead to gender
             they may not retain control over the assets:                inequalities in access to and adoption of
             White (1991) found that about 50 percent of                 new technologies, as well as in the use of
             loans taken by women were used for men’s                    purchased inputs and existing technologies.
             productive activities; Goetz and Gupta (1996)                  The use of purchased inputs depends on the
             reported that, on average, women retained                   availability of complementary assets such as
             full or significant control over loan use in                land, credit, education and labour, all of which
             only 37 percent of all cases; while Chowdhury               tend to be more constrained for female-headed
             (2009) reported that credit to women from                   households than for male-headed households.
             the Grameen Bank was positively and                         The adoption of improved technologies is
             significantly correlated with the performance               positively correlated with education but is also
             of male-managed micro-enterprises but not                   dependent on time constraints (Blackden et al.,
             those managed by females.                                   2006). In an activity with long turnaround
                In Eastern Asia, the evidence regarding                  periods, such as agriculture, working capital
             bias in credit access is mixed. In China, de                is required for purchasing inputs such as
             Brauw et al. (2008) found that households                   fertilizers and improved seeds; however, as
             in which women manage their own farms                       discussed above, women face more obstacles
             appear to have almost identical access to                   relative to men in their access to credit.
             land and credit relative to male-headed                     Adoption of improved technologies and inputs
             households. On the other hand, a joint study                may also be constrained by women’s lower
             by FAO and the United Nations Development                   ability to absorb risk.
             Programme (FAO/UNDP, 2002) carried out                         The evidence points to significant gender
             in Viet Nam indicates that female-headed                    differences in the adoption of improved
             households borrow less, have less access to                 technologies and the use of purchased inputs
             formal credit and pay higher interest on                    across regions (see Peterman, Quisumbing
             loans than dual-headed households.                          and Behrman, 2010, for a comprehensive
                For Latin America, Fletschner (2009)                     literature review). For example, male-
             reports that in Paraguay women in farm                      headed households show much wider use of
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                                                                                                                                            35
fertilizers than their female counterparts in                In Burkina Faso, women use less fertilizer per
all countries covered (Figure 14). While the                 hectare than men (Udry et al., 1995).
direction of the difference is unambiguous                      Studies that disaggregate mechanization
across technologies and regions, the degree                  – tools and other farming equipment – by
of inequality shows notable variations,                      gender are rare. This may, in part, be because
appearing much more pronounced in                            modern farming equipment such as tractors
Southern Asia (Bangladesh and Pakistan) and                  and tillers are not commonly available to any
in West Africa (Ghana and Nigeria).                          farmer, especially in sub-Saharan Africa. The
   Detailed country studies provide deeper                   share of farmers using mechanical equipment
insights. In Ghana, for example, Doss and                    and tools is quite low in all countries, but it
Morris (2001) found that only 39 percent                     is significantly lower for farmers in female-
of female farmers adopted improved crop                      headed households, sometimes by very wide
varieties (compared with 59 percent of male                  margins (Figure 15).
farmers) because they had less access to land,                  A few studies from the late 1980s and
family labour and extension services. Several                early 1990s point to gender differences
studies from Kenya show that female-headed                   in ownership of, or access to, tools. In a
households have much lower adoption rates                    Gambian irrigated rice scheme, none of
for improved seeds and fertilizers. These                    the women owned a plough and fewer
differences are explained by reduced access                  than 1 percent owned a weeder, seeder or
to land and labour, lower education levels                   multipurpose cultivation implement; the
and limited access to credit markets (Kumar,                 proportions of men owning these tools
1994; Saito, Mekonnen and Spurling, 1994;                    were 8, 12, 27 and 18 percent, respectively
Ouma, De Groote and Owur, 2006). Credit                      (von Braun, Hotchkiss and Immink, 1989).
constraints also limit the access of female-                 According to data from a household survey
headed households to fertilizers in Benin and                across three Kenyan districts, the value of
Malawi (Minot, Kherallah and Berry, 2000).                   farm tools owned by women amounted to


     FIGURE 14
     Fertilizer use by female- and male-headed households


        Bolivia
       Ecuador
    Guatemala
     Nicaragua
       Panama

   Bangladesh
         Nepal
      Pakistan
     Tajikistan
     Viet Nam

       Ghana
   Madagascar
      Malawi
      Nigeria
                  0        10         20         30         40         50         60          70         80         90

                                           Percentage of households using fertilizers



                       Female-headed households                               Male-headed households

Note: Calculations made using nationally representative household surveys. Differences between female- and male-headed
households are significant at the 95 percent confidence level for all countries.
Sources: FAO, RIGA team, and Anríquez, 2010.
36   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                   FIGURE 15
                   Mechanical equipment use by female- and male-headed households

                    Ecuador
                 Guatemala
                  Nicaragua
                    Panama

                Bangladesh
                 Indonesia
                      Nepal
                  Tajikistan
                  Viet Nam

                      Ghana
               Madagascar
                  Malawi
                  Nigeria

                                0          5        10         15        20     25      30       35      40       45       50

                                                         Percentage of households using mechanization



                                        Female-headed households                          Male-headed households

            Note: Calculations made using nationally representative household surveys. Differences between female- and male-headed
            households are significant at the 95 percent confidence level for all countries.
            Sources: FAO, RIGA team, and Anríquez, 2010.


             only 18 percent of the tools and equipment                          It is important to note that not all types
             owned by male farmers (Saito, Mekonnen                           of female-headed households are equally
             and Spurling, 1994).                                             constrained in their access to technology. On
               In a more recent study of productivity                         small farms in Kenya, households headed by
             differences by gender in a rice irrigation                       single, divorced or widowed women are the
             scheme in Central Benin, researchers noted                       least likely to use animal traction. In contrast,
             that equipment such as motor cultivators                         female-headed households in which the
             used for ploughing and transport were                            husband lives elsewhere are more likely to
             managed by groups, but women’s groups                            use animal traction and hired labour, because
             were unable to start ploughing until the                         they still benefit from their husband’s
             drivers had completed work on men’s fields.                      name and social network and often receive
             As a consequence of the delays in ploughing                      remittances from him (Wanjiku et al., 2007).
             and planting, women faced yield losses and
             could not participate in a second cropping
             season (Kinkingninhoun-Mêdagbé et al.                            Key messages
             2010). Gender differences in the use of farm
             equipment may have further implications.                           •	 Across diverse regions and contexts,
             Quisumbing (1995), for example, concludes                             women engaged in agriculture face
             that farmers with more land and tools are                             gender-specific constraints that limit
             more likely to adopt other technologies, thus                         their access to productive inputs,
             highlighting the complementarities among                              assets and services. Gender gaps are
             agricultural inputs.                                                  observed for land, livestock, farm labour,
               Furthermore, lack of access to                                      education, extension services, financial
             transportation technology often limits the                            services and technology.
             mobility of women and their capacity to                            •	 For those developing countries for which
             transport crops to market centres (Box 7).                            data are available, between 10 percent
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                                                                                                                                  37
BOX 7
Smallholder coffee production and marketing in Uganda


Coffee is Uganda’s largest export,                 much smaller scale, women sold smaller
providing employment (directly and                 amounts than men (only 47 kg, on average,
indirectly) to an estimated 5 million people       compared with 151 kg for men).
(Bank of Uganda, 2001; Kempaka, 2001).               Most smallholders sold their coffee in
Smallholders’ coffee is usually intercropped       the form of dry cherries locally known
with staples such as banana, plantain,             as kiboko, which would then be milled
beans, sweet potatoes and maize. Simple            by the traders who bought the coffee.
farming methods are normally used to               Some farmers transported their coffee to
produce coffee; purchased inputs such as           market, which allowed them to sell it at
fertilizer or pesticides are used minimally        a higher price. Members of male-headed
and irrigation is rare.                            households were more likely than those
  A study by Hill and Vigneri (2009)               of female-headed households to travel to
draws on a sample of 300 coffee-farming            market to sell their coffee. Fifteen percent
households that were surveyed in 1999              of the transactions made by male-headed
and 2003. Twenty-three percent of the              households took place in the nearby coffee
households were headed by females                  market, compared with only 7 percent
(mainly widows, but also unmarried,                of transactions by women. This may be
separated and divorced women). Female-             because men were more likely to own a
headed households had less labour,                 bicycle and could therefore travel to the
land and coffee trees than male-headed             market more easily than women. Farmers
households; they also had lower levels of          received a higher price for their coffee if
wealth and education. Women household              they chose to mill it at the market before
heads tended to be older; many were                selling it. Only 3 percent of transactions
wives who had taken over when their                were for milled coffee, all of which were
husband had died. As a result of these             made by male-headed households.
basic differences in scale, liquidity and            The study concludes that gender
human capital, we may expect crop choice,          differences in marketing are largely
production methods and access to markets           explained by the fact that women market
to be quite different for male- and                smaller quantities of coffee and do not
female-headed households.                          own bicycles. It also finds that a major
  The share of labour allocated to coffee          constraint facing women is their relative
production and the proportion of trees             difficulty in accessing marketing channels
harvested were comparable between male-            that allow added value. By engaging in
and female-headed households, as was the           marketing channels in which they add
yield per producing tree. However, because         value, male-headed households received
female-headed households farmed on a               7 percent more per kilogram of coffee.



   and 20 percent of all land holders are               half to two-thirds the size of farms
   women, although this masks significant               operated by male-headed households.
   differences among countries even                  •	 The livestock holdings of female farmers
   within the same region. The developing               are much smaller than those of men in
   countries having both the lowest and                 all countries for which data are available,
   highest shares of female land holders are            and women earn less than men from
   in Africa.                                           their livestock holdings. Women are
•	 Among smallholders, farms operated by                much less likely to own large animals,
   female-headed households are smaller                 such as cattle and oxen, that are useful as
   in almost all countries for which data are           draught animals.
   available. The gap is negligible in some          •	 Farms run by female-headed households
   countries, but in others farms operated              have less labour available for farm work
   by female-headed households are only                 because these households are typically
38   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                  smaller and have fewer working-age adult               •	 Smallholders everywhere face constraints
                  members and because women have heavy                      in accessing credit and other financial
                  and unpaid household duties that take                     services, but in most countries the share
                  them away from more productive activities.                of female smallholders who can access
               •	 Education has seen improvements in                        credit is 5–10 percentage points lower
                  gender parity at the national level,                      than for male smallholders. Access to
                  with females even exceeding male                          credit and insurance are important for
                  attainment levels in some countries, but                  accumulating and retaining other assets.
                  in most regions women and girls still lag              •	 Women are much less likely to use
                  behind. The gender gap in education is                    purchased inputs such as fertilizers
                  particularly acute in rural areas, where                  and improved seeds or to make use of
                  female household heads sometimes have                     mechanical tools and equipment. In
                  less than half the years of education of                  many countries women are only half as
                  their male counterparts.                                  likely as men to use fertilizers.
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                                                                                                                                             39
4.	 Gains from closing
    the gender gap


Many studies show that yields on plots                        based discrimination. Countries with lower
managed by women are lower than those                         levels of gender inequality tend to achieve
managed by men. This is not because                           higher average cereal yields than countries
women are worse farmers than men. Indeed,                     with higher levels of inequality (Figure
extensive evidence shows that women are                       16). Of course, the relationship shows only
just as efficient as men. They simply do not                  correlation, not causation, and the direction
have access to the same inputs. If they did,                  of causality could run in either direction (or
their yields would be the same as men’s, they                 in both directions). In other words, more
would produce more and overall agricultural                   equal societies tend to have more productive
production would increase.                                    agriculture, but more productive agriculture
  The relationship between gender                             can help reduce gender inequality.
equality and agricultural productivity can                      Research surveyed below confirms that
be explored using OECD’s index of Social                      closing the gender gap in agriculture can
Institutions and Gender Inequality (SIGI)                     improve agricultural productivity, with
(OECD, 2010). The SIGI index reflects social                  important additional benefits through
and legal norms such as property rights,                      raising the incomes of female farmers,
marital practices and civil liberties that                    increasing the availability of food and
affect women’s economic development. A                        reducing food prices, and raising women’s
lower SIGI indicates lower levels of gender-                  employment and real wages.


     FIGURE 16
     Cereal yield and gender inequality


     Cereal yield (tonnes/ha)
     4

   3.5

     3

   2.5

     2

   1.5

     1

   0.5

     0
           1st       2nd        3rd        4th        5th        6th        7th        8th         9th       10th

                 SIGI group: 1st = least gender inequality to 10th = greatest gender inequality


Notes: Gender inequality is a measure used by the Social Institutions and Gender Index (SIGI), a composite measure of
gender discrimination based on social institutions, constructed by the OECD Development Centre.
Sources: Cereal yield: FAO, 2010b; SIGI group: OECD, 2010.
40   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                                                                            labour, the plots controlled by women used
             Productivity of male and female                                less of all other inputs: men’s and children’s
             farmers                                                        labour, draught animal labour and organic
                                                                            and chemical fertilizers. Women’s yields
             Many studies have attempted to assess                          were lower than men’s for a variety of
             whether female farmers are as productive                       crops – 20 percent lower for vegetables and
             as male farmers. These studies measure                         40 percent lower for sorghum – but the
             productivity in a variety of ways, but the                     difference was explained entirely by their
             most common method is based on output                          lower use of productive inputs, which in turn
             per hectare of land, or yield. Simply                          was a result of gender-specific social norms.
             comparing yields on men’s and women’s                          The authors estimated that increasing input
             farms can reveal differences between the                       use on women’s plots could increase overall
             two groups – women typically achieve                           output by 10–20 percent (Udry et al., 1995).
             lower yields than men do – but it does not                     Further analysis of the same data found that
             explain why. The most thorough studies also                    overall household production could have
             attempt to assess whether these differences                    been almost 6 percent higher if resources
             are caused by difference in input use, such                    were reallocated towards women’s plots
             as improved seeds, fertilizers and tools, or                   (Udry, 1996).
             other factors such as access to extension                        Two additional studies from Burkina
             services and education. The vast majority                      Faso provide a deeper understanding of
             of this literature confirms that women are                     these issues. The first found that female
             just as efficient as men and would achieve                     farmers produced 15 percent lower value
             the same yields if they had equal access to                    per hectare than male farmers. It also found
             productive resources and services.                             that female farmers needed advice from
               A thorough literature search identified                      female agricultural extension workers – not
             27 studies that compare the productivity                       just more inputs – in order to achieve higher
             of male and female farmers.10 These                            yields, confirming the complementarities
             studies covered a wide range of countries                      among the broad range of assets and services
             (primarily, but not only, in Africa), crops,                   required for agricultural production (Bindlish,
             time periods and farming systems, and                          Evenson and Gbetibouo, 1993). The second
             used various measures of productivity and                      reconsidered the data from Udry (1996)
             efficiency. Despite this variety, most found                   and supplemented them with more recent
             that male farmers achieved higher yields                       nationally representative data. It found
             than female farmers. The estimated yield                       that households located in less favourable
             gaps ranged widely but many clustered                          production zones or in areas suffering
             around 20–30 percent, with an average of                       from drought tended to allocate resources
             25 percent.11                                                  between male- and female-managed plots
               Most of the studies found that differences                   more efficiently than households in more
             in yields were attributable to differences in                  favourable areas, perhaps because the risk
             input levels, suggesting that reallocating                     associated with being inefficient was higher
             inputs from male to female plots can                           for them (Akresh, 2008).
             increase overall household output. Several                       Research in the Ethiopian highlands found
             studies showed this explicitly. Because                        that female-headed households produced
             this literature is complex and somewhat                        35 percent less per hectare, in value terms,
             contentious, it is summarized below.                           than male-headed households but the
               One of the most influential studies in                       differences were due to lower levels of input
             this field comes from Burkina Faso. The                        use and less access to extension services by
             authors compared 4 700 agricultural plots                      the female farmers (Tiruneh et al., 2001). In
             in six villages. With the exception of own-                    the same region, yields for barley and other
                                                                            cereals were found to be 50 percent higher
             10	
                 For more detailed surveys of this literature, see          for farms operated by men because farms
             Quisumbing (1996) and Peterman, Quisumbing and                 run by female-headed households had only
             Behrman (2010).
                                                                            half the male labour and less than one-third
             11	
                 Not all of the 27 studies quantified the yield gap. Some
             provided estimates for a single crop while others reported     of the amount of draught animal power
             on multiple crops.                                             (Holden, Shiferaw and Pender, 2001).
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                                                                                                                                   41
  Women in Ghana were found to be                   of lower quality or higher price (Timothy and
as efficient as men in maize and cassava            Adeoti, 2006).
production, but they achieved lower yields             Additional studies in sub-Saharan Africa
and earned lower profits because they               from Cameroon (Kumase, Bisseleua and
could not maintain the fertility of their land      Klasen, 2008), Benin (Kinkingninhoun-
(Goldstein and Udry, 2008). People who are          Mêdagbé et al., 2010), Côte d’Ivoire (Adesina
disadvantaged in the social and political           and Djato, 1997) and Zimbabwe (Horrell and
networks of their villages – like many female       Krishnan, 2009) also overwhelmingly support
household heads – are more likely to have           the conclusion that differences in farm
their land expropriated if they allow it to         yields between men and women are caused
remain fallow, so they tend to keep their           primarily by differences in access to resources
land under cultivation continuously, eroding        and extension services.12
soil fertility (Goldstein and Udry, 2008).             Evidence from other regions is relatively
Several studies from Ghana also confirm             rare because farming operations are less
that male and female cocoa producers have           likely to be segregated by gender than is
the same yields when input use is the same          the case in Africa, but the available studies
(Quisumbing and Otsuka, 2001b; Hill and             generally support the finding that female
Vigneri, 2009).                                     farmers are at least as efficient as their
  Men producing maize, beans and cowpeas            male counterparts. For example, female-
in Kenya achieve higher gross value of              managed farms in Nepal produce less value
output per hectare than women, but the              per hectare than male-managed farms, but
difference is accounted for by differences in       the differences are nearly all accounted for
input use (Saito, Mekonnen and Spurling,            by lower input use (Thapa, 2008). Female-
1994). In western Kenya, female-headed              managed farms in China are at least as
households were found to have 23 percent            profitable as those run by men, according to
lower yields than male-headed households,           data from the China National Rural Survey
but the difference was caused by less-secure        (Zhang, De Brauw and Rozelle, 2004).
access to land and lower education levels              Some studies compare labour productivity
(Alene et al., 2008). An earlier study of           rather than yields, but the results are
smallholder farmers in western Kenya found          consistent with the finding that yield
that women’s maize yields were 16 percent           differences are caused by differences in input
lower than men’s, largely because they used         use. The labour productivity of female farm
substantially less fertilizer (Ongaro, 1990).       workers in Bangladesh is at least as high as
  A nationally representative study in              that of male workers when input use is the
Malawi found that maize yields were                 same (Rahman, 2010). Labour productivity
12–19 percent higher on men’s plots, but            studies for oil palm in Indonesia (Hasnah,
when women were given the same level of             Fleming and Coelli, 2004), for rice in Nepal
fertilizer for use on experimental plots, they      (Aly and Shields, 2010) and for vegetables in
achieved the same yields (Gilbert, Sakala and       Turkey (Bozoglu and Ceyhan, 2007) all show
Benson, 2002).                                      that female labour is at least as productive
  Considerable evidence is available from           as male labour when differences in irrigation
Nigeria from several states and for a wide          and seed type are considered.
variety of crops. In Oyo State, male and
female farmers growing maize, yam, cassava,
vegetables and legumes were found to be             Production gains from closing the
equally productive (Adeleke et al., 2008). In       gender gap
Osun State, female rice producers achieved
66 percent lower yields than male farmers           If gender-specific differences in input use
but the difference was attributable to              could be overcome and female farmers could
differences in input use (Oladeebo and              achieve the same yields as male farmers, the
Fajuyigbe, 2007). Similarly, in Ondo and
Ogun States, female small-scale cassava             12	
                                                        Some studies could not fully account for yield differences
                                                    between male and female farmers because they did not
farmers achieved lower yields and lower
                                                    consider all the resource gaps women face (Zavale, Mabaye
returns than their male counterparts because        and Christy [2006], Uaiene and Channing [2009], and Lilja,
they used fewer inputs and purchased inputs         Randolph and Diallo [1998]).
42   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




             evidence suggests that the production gains                    countries where the gender gap is wider.
             could be substantial. The potential gains                      Increasing women’s access to land as well as
             cannot be calculated precisely because the                     complementary inputs in that case would
             necessary data are not available; however,                     generate broader socio-economic benefits
             a reasonable range can be estimated based                      than those captured by this analysis.
             on the yield gaps identified in the studies                       This approach provides admittedly
             discussed above and the amount of farm                         very rough estimates, but they suggest
             land that women manage.                                        that closing the gender productivity gap
               As noted above, studies of the yield gap                     could increase agricultural output in the
             between male and female farmers provide                        developing world by a significant amount.
             estimates averaging 20–30 percent, and most                    Increased production would also imply
             attribute the difference to lower levels of                    increased food availability and reductions
             input use. Although most of these studies                      in undernourishment. The standard
             pertain to sub-Saharan Africa, similar input                   methodology used by FAO to estimate the
             gaps have been documented for all regions                      number of people who are undernourished
             in Chapter 3. Therefore, it is reasonable to                   calculates the average daily dietary energy
             assume that a similar range of yield gaps                      supply available for consumption in each
             exists in other regions. Closing the input                     country and applies country-specific criteria
             gap on the agricultural land held by women                     for its distribution and thresholds for
             could increase yields on their land to the                     minimum per capita energy requirements
             levels achieved by men. This would imply                       (see FAO, 2002 for details). People who
             an increase in production of 20–30 percent                     fall below this minimum threshold are
             on their land, and increases at the national                   considered chronically undernourished.
             level proportionate to the amount of land                      Domestic food production is a key
             controlled by women. This would increase                       component of the dietary energy supply,
             agricultural output in the developing                          so – assuming that the additional output
             countries for which data are available by an                   from closing the gender gap is consumed
             average of 2.5–4 percent.13 Assuming that                      domestically – closing the gender yield gap
             the input and yield gaps are representative                    could have a direct impact on reducing the
             of other developing countries, this would                      number of people who are undernourished.
             imply global gains of a similar magnitude.                        Inserting the potential output gains
               Of course, the potential production                          calculated above into the formula for
             gains calculated by this method are based                      estimating the number of undernourished
             on the existing distribution of land and a                     provides a rough quantitative estimate of
             stylized yield gap of 20–30 percent. This                      how closing the gender gap in agriculture
             implies that countries where women control                     could contribute to reducing hunger. If
             proportionately more land could achieve                        yield gaps of 20–30 percent were closed
             the greatest potential gains. It may be the                    and domestic production increased by 2.5–
             case, however, that the overall gender gap                     4 percent, the number of undernourished
             in access to agricultural resources is, in fact,               people in the countries for which data are
             wider where women control less land. The                       available could decline by 12–17 percent.14
             actual gains from closing the gender gap                       An estimated 925 million people in the world
             in access to resources would be greater in                     were undernourished in 2010, of which
                                                                            906 million were in developing countries
                                                                            (FAO, 2010g), Gains of this magnitude could
             13
                 Data on the share of women agricultural holders
             are available for 52 countries. The methodology for
                                                                            therefore equate to 100–150 million fewer
             calculating potential gains starts with the definition of      people living in hunger. For countries where
             output (Q) as yield (Y) times area (A), Q = Y*A. Next, for     hunger is more widespread and women play
             the 20 percent productivity gap scenario, assume that          a major role in the agriculture sector, the
             women farmer’s yields are only 80 percent those of men,
             i.e. Yf = 0.8*Ym. (The subscripts f and m denote female        proportional declines could be even greater.
             and male, respectively.) Now write Q=Y*A as Q = Yf *P*A
             + Ym*(1-P)*A, where P is the share of land cultivated by
             women farmers. Solve this problem for Ym and then use
             Yf = 0.8*Ym to obtain Yf. Assuming the gender gap in           14	
                                                                                Data for both the share of women agricultural holders
             productive assets is closed, set Yf equal to Ym and find the   and the number of people undernourished are available for
             new output level, Q*.                                          34 countries.
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                                                                                                                                          43
  These potential output gains would                       contributes positively and significantly
only be the first, direct, effect. Over time,              to household food consumption (Garcia,
higher productivity would have additional                  1991). This was reinforced by evidence
impacts such as increased demand by                        from Brazil, which showed that maternal
farmers for labour and locally produced                    income exerts a larger effect on children’s
goods and services (Hayami et al., 1978;                   nutritional outcome indicators than paternal
FAO, 2004). Additional output could result                 income and that women spend considerably
in lower commodity prices, depending on                    more than men on education, health,
the responsiveness of demand and the                       and household services (Thomas, 1997). In
degree of trade openness. Most households                  extended family households in Mexico, the
in developing countries, including in rural                impact of increasing family income on the
areas, are net food buyers and would gain                  nutritional status of children depends on
from a fall in staple food prices. Farm                    who earns the income; higher earnings by
incomes could suffer, on the other hand,                   any female household member – not only
unless markets are sufficiently developed so               mothers – has substantial positive impacts
as to handle the additional supply.                        on child nutrition, while this is not the case
                                                           for male income earners (Djebbari, 2005).
                                                           More recent evidence from Malawi confirms
Other social and economic benefits                         that increasing women’s – but not men’s –
of closing the gender gap                                  access to credit increases total household
                                                           expenditures on food and improves the long-
In addition to increases in production and                 term food security of young female children
income, closing the gender gap in agriculture              (Hazarika and Guha-Khasnobis, 2008).
would generate broader social and economic                   The fact that gender inequality is
benefits by strengthening women’s direct                   particularly severe in Southern Asia helps
access to, and control over, resources and                 explain, at least partly, why rates of child
incomes. Evidence from Africa, Asia and Latin              malnutrition there are twice those found
America consistently shows that families                   in sub-Saharan Africa (Smith et al., 2003).
benefit when women have greater status                     Indeed, despite surpassing sub-Saharan
and power within the household. Increased                  Africa in terms of national income,
control over income gives women a stronger                 democracy, food supplies, health services
bargaining position over economic decisions                and education, Southern Asia still trails in
regarding consumption, investment and                      child malnutrition. This has been labelled
production. When women have more                           the “Asian enigma”, which finds women’s
influence over economic decisions, their                   status, sanitation and urbanization to be
families allocate more income to food,                     the key factors in narrowing the gap in
health, education, children’s clothing and                 children’s nutritional status. Recent evidence
children’s nutrition.15 Social safety-net                  from Bangladesh confirms that children’s
programmes in many countries now target                    long-term nutritional status is higher
women specifically for these reasons (Box 8).              in households where women are more
  A large number of studies have linked                    empowered (Bhagowalia et al., 2010).
women’s income and greater bargaining                        Improved gender equality in access to
power within the family to improved child                  opportunities and returns to assets not only
nutritional status, which in turn influences               improve nutrition, health and education
health outcomes and educational attainment                 outcomes, but can also have a long-lasting
(Smith et al., 2003). Evidence from the                    impact on economic growth by raising
Philippines provided some of the earliest                  the level of human capital in society.16
data showing that increasing the share                     Closing the gender gap spurs economic
of household income earned by mothers                      development, largely through the impact
                                                           of female education on fertility, child
15
   Important studies in this field include Behrman and
Deolalikar (1988), Behrman and Wolfe (1989), Kennedy
and Peters (1992), Kennedy and Haddad (1994), Hoddinott    16
                                                              Important studies in this field include Dollar and Gatti
and Haddad (1995), Thomas (1997), Haddad (1999), Katz      (1999), Klasen (2002), Knowles, Lorgelly and Owen (2002),
(2000), Quisumbing and Maluccio (2000), Smith et al.       Kalaitzidakis et al. (2002), Lagerlöf (2003) and Klasen and
(2003) and Doss (2005).                                    Lamanna (2009).
44   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                BOX 8
                Targeting transfer payments to women for social benefits


                Conditional transfer programmes are a                    the education, nutrition, and /or well-being
                type of safety net programme in which                    of their children. Post-factum evaluations
                cash or benefits in kind are transferred to              of conditional transfer programmes have
                generally poor households on condition                   confirmed this to be the case: the impact
                that the household undertake certain                     on spending patterns goes beyond the
                types of human capital investment for                    simple income effect of the transfer, with
                the benefit of their children. Women are                 recipient households spending a larger
                often targeted as the recipients of such                 proportion of their incomes on food
                payments because evidence shows they                     (Schady and Rosero, 2008) and a relatively
                are more likely than men to prioritize                   larger proportion on more nutritious food
                child nutrition. The types of investments                (Macours, Schady and Vakis, 2008).
                generally considered are in health – i.e.                   An implicit, yet important, idea
                pre- and post-natal health care, health                  underlying these programmes is that by
                check-ups or attendance at health                        directing the transfers to mothers, they
                clinics – and in education – generally                   strengthen the bargaining position of
                measured by enrolment and attendance                     women in the intra-household decision-
                rates. Conditional transfer programmes                   making process. Some conditional
                have rapidly gained popularity in the                    transfer programmes successfully also
                developing world. Starting from the                      target gender inequality directly. In
                Oportunidades (formerly known as                         Bangladesh and Pakistan, programmes
                PROGRESA – Education, Health and                         exist to promote girls’ enrolment in public
                Nutrition Programme) programme in                        education. In Bangladesh, the Female
                Mexico in 1997, they have expanded                       Secondary School Assistance Project
                worldwide, with all developing regions                   (FSSAP) provides a stipend to girls aged
                having some active conditional transfer                  11–18 years for attending secondary
                programme, although with the largest                     school, while in Pakistan, the Punjab
                prevalence in Latin America.                             Education Sector Reform Programme
                   Conditional transfer programmes can                   (PESRP) provides “scholarships” for
                be used directly and indirectly to address               girls aged 10–14 to attend school. Both
                gender inequities. With the exception of a               programmes have been very successful
                few secondary school programmes, in the                  in increasing enrolment: Khandker,
                great majority of them the beneficiaries are             Pitt and Fuwa (2003) estimate that the
                the mothers. This choice is founded on the               FSSAP increased the enrolment of girls
                overwhelming evidence that, when women                   by 12 percentage points, while the PESRP
                and mothers control a higher proportion                  increased it by 11 percentage points,
                of household income, families tend to                    according to an evaluation by Chaudhury
                spend a higher share of their budgets on                 and Parajuli (2010).



             mortality and the creation of human capital                 men and women, will again work to raise
             in the next generation. Falling fertility                   the level of human capital available in
             rates will, after some years, lead to what                  the working population. These growth
             Bloom and Williamson (1998) have termed                     studies suffer from the usual limitations:
             the “demographic gift”. The working-age                     it is impossible to assign the direction of
             population will grow faster than the rest of                causality, and it could also be the case
             the population, reducing dependency rates                   that higher growth causes countries to
             and thus benefiting per capita growth.                      reduce gender inequality by economically
               It is also true that removing the gender                  empowering women. Nonetheless, the point
             gap in access to opportunities widens the                   remains that closing the gender gap in
             pool of talent available, which, assuming                   educational and employment opportunities
             that the talent is distributed equally among                would boost long-term growth.
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                                                                                                                                  45
                                                      •	 Increasing agricultural production
Key messages                                             by this magnitude could reduce the
                                                         number of undernourished people
 •	 Female farmers are just as efficient as              by 12–17 percent, and would imply
    male farmers but they produce less                   significant progress towards achieving
    because they control less land, use fewer            MDG 1C. This highlights the synergies
    inputs and have less access to important             that exist between promoting gender
    services such as extension advice.                   equality and reducing extreme poverty
 •	 Closing the gender gap in access and                 and hunger.
    use of productive resources and services          •	 When women control additional
    would unlock the productivity potential              income, they spend more of it than
    of women and could increase output                   men do on food, health, clothing and
    substantially. Closing the gap could                 education for their children. This has
    increase agricultural output in the                  positive implications for immediate
    developing world by 2.5–4 percent, on                well-being as well as long-run human
    average, with higher gains in countries              capital formation and economic growth
    where women are more involved in                     through improved health, nutrition and
    agriculture and the gender gap is wider.             education outcomes.
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             5.	 Closing the gender gap in
                 agriculture and rural employment


             Closing the gender gap in agriculture is                         them. In the parts of sub-Saharan Africa
             not an easy task, but progress can be made                       where customary property regimes prevail,
             and simple interventions can sometimes                           community leaders tend to favour males over
             be very powerful. Carefully designed                             females in the allocation of land, both in
             policies, strategies and projects can work                       terms of quantity and quality. Where private
             within existing cultural norms, through                          property prevails, cultural norms generally
             the public and private sectors, in ways that                     dictate that men own and inherit land while
             benefit both women and men (Box 9).                              women gain access to land through their
             Specific recommendations for closing the                         relationship with a male relative.
             gender gap in access to land, rural labour
             markets, financial services, social capital and                  Eliminate discrimination under the law
             technology include the steps outlined below.                     Where statutory legal rights to land remain
                                                                              gender-biased, a key strategy is to review
                                                                              and reform all national legislation that
             Closing the gap in access to land17                              relates to land and natural resources.
                                                                              Although land laws are the starting point,
             Governments have long recognized the                             related legislation should also be considered.
             importance of secure land tenure in                              Family and marriage laws, inheritance
             promoting equitable, sustainable agricultural                    provisions and housing law are all important
             development. Women have not always                               legal areas that play a supporting role in
             benefited from general land distribution and                     ensuring equitable treatment of men and
             titling efforts, however, and in some cases                      women in control over land.18
             have seen their customary rights eroded as
             formal rights have been extended to male                         Recognize the importance and power of
             heads of household. Many governments have                        customary land rights
             attempted to strengthen women’s tenure                           Many countries have extended formal legal
             rights within marriage and as individuals,                       rights to women over land inheritance and
             but these efforts are often frustrated by a                      ownership, but customary practices – and
             combination of legal and cultural practices                      the inability of many women to assert
             that still favour men.                                           their legal rights – mean that formal legal
                In Latin America, for example, inheritance                    provisions are often not followed. In many
             is the most frequent source of transfer of                       countries, tradition is stronger than law
             ownership of land, but daughters are much                        when it comes to land issues. Opposition
             less likely than sons to inherit land. Many                      from land reform authorities, peasant unions,
             countries in the region have instituted legal                    village authorities and male household
             reforms that have strengthened married                           heads can frustrate land reform efforts to
             women’s land rights, but land-titling efforts                    extend legal land rights to both single and
             have not always facilitated the practice of                      married women. Legal rights are difficult to
             including both husbands’ and wives’ names.                       enforce if they are not seen as legitimate;
             In Asia, women typically have legal rights to                    thus recognizing customary land rights and
             land ownership, but often struggle to assert                     working with community leaders is essential
                                                                              to ensure that women’s rights are protected.
             17
                This section is based on FAO (2010h), which provides an
             extensive review of the relevant literature. Important studies
             in this field include Agarwal (1994), Agarwal (2003),            18
                                                                                	 Additional information on women and their status under
             Lastarria-Cornhiel (1997), Deere (2003), Deere and León          the law is available at the World Bank website “Women,
             (2003), and Deere and Doss (2006).                               business and the law” (http://wbl.worldbank.org/).
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                                                                                                                                     47
  BOX 9
  Mama Lus Frut: working together for change


  Palm oil production in Papua New Guinea             collection to take into account women’s
  is dominated by smallholder farmers,                time constraints. Then they distributed
  and harvesting oil palm trees is highly             special nets that made it easier to carry
  differentiated by gender: men cut fresh             the loose fruits to the roadside. Neither
  fruit bunches from the trees, while women           initiative was successful, because they did
  collect loose fruits from the ground and            not correctly assess why women were not
  carry them to the roadside where they               collecting the fruit.
  are picked up by operators from the mill.             Finally, the Mama Lus Frut scheme
  These gender roles are firmly engrained in          was introduced in 1997 to ensure that
  the local culture and institutions.                 women received payment for their work.
     Family labour is mobilized for the               Women received individual harvest nets
  harvest. While it was implicitly assumed            and harvest payment cards, and they
  in the past that the household head                 received their own monthly income
  would compensate family members for                 based on the weight of the fruit they
  their labour with the income gained from            collected, deposited directly into their
  oil palm production, in reality, female             personal bank accounts. As a result, the
  household members were often not being              number of women participating in the
  compensated for their work. In many cases,          scheme more than doubled and the
  this led to intra-household struggles and           amount of loose fruits delivered to the
  to women withdrawing their labour from              mills increased significantly. By 2001,
  loose fruit collection and focusing instead         26 percent of smallholder income from
  on vegetable production, which allowed              oil palm was directly paid to women. Men
  them to earn, and keep, an income.                  reacted positively because the gender
     The local oil palm industry realized that        division of labour remained unchanged
  between 60 and 70 percent of loose fruit            and intra-household conflicts over palm oil
  were not being collected. The industry              harvesting decreased.
  tried to raise the share of loose fruits in
  total harvest through several initiatives.          Sources: Kosczberski, 2001, and Warner and
  First, they delayed the timing of loose fruit       Bauer, 2002.



Indeed, strengthening traditional use-rights          and courts. Gender-balanced employment
for widows and divorced women may provide             in these institutions can also help. Where
more secure tenure for them even in cases             appropriate, officials’ performance should
where there is resistance to full ownership.          be evaluated against gender-related targets.
                                                      The involvement of women’s organizations in
Educate officials and evaluate them on                the process can facilitate the achievement of
gender targets                                        gender equity targets. Furthermore, gender
Local land officials may be unaware of                targets for access and tenure security should
gender equity laws and objectives or lack             be monitored and officials held accountable
the mechanisms, tools and will to implement           for meeting them.
them. Legislation needs to be supported                  In Nicaragua the property legalization
by regulations and gender-specific rules              process, which the women’s affairs office
and guidelines that educate officials in              helped coordinate, included gender
agriculture ministries, land institutions and         sensitization training for officials and
other agencies regarding the implementation           information campaigns on the inclusion of
of the gender position of the law. Relevant           women in the process (FAO, 2010h). This
training is also required for staff in the            has helped raise awareness and acceptance
various institutions that carry out and enforce       among men and women of women’s land
land rights, including land registries, cadastral     rights, although several rounds of training
offices, titling agencies, land magistrates           were necessary.
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             Educate women regarding land rights                         of women in local government. The 2003
             Raising women’s legal literacy, increasing                  constitution mandates that 30 percent of all
             the dissemination and accessibility of                      decision-making representatives be women.
             information and establishing supporting                        Similarly, in the United Republic of
             legal services are essential in promoting                   Tanzania, village land councils, which settle
             gender equity in land programmes. Legal                     land disputes, comprise seven members, of
             literacy means that women are aware of                      whom three must be female (Ikdahl, 2008).
             their legal rights and know how they can be                 Ethiopia’s land certification process has
             enforced and protected. Officials responsible               been hailed as effective, low-cost, rapid and
             for implementing land programmes must                       transparent, and gender equity goals have
             actively educate both men and women                         been advanced because land administration
             regarding gender equity provisions and                      committees at the local level are required to
             the possibility of joint titling, rather than               have a least one female member.
             treating the decision as a private matter                      In the Lao People’s Democratic Republic,
             between spouses (Ikdahl, 2008; Brown, 2003).                women were not receiving titles until the
                Civil society organizations can be                       Lao Women’s Union started to participate
             instrumental in promoting legal literacy. In                in the land-titling programme. The Union
             Mozambique, when land legislation was                       works at the national and local levels and
             integrated into literacy programmes or when                 has been active in informing both men and
             non-governmental organizations (NGOs)                       women about the titling process and their
             distributed land law information repeatedly                 legal rights, as well as helping to formulate
             over a long time, women were more likely to                 gender-sensitive procedures and train local
             know their rights to land (FAO, 2010h).                     field staff in their application.
                Precisely because they are so important,                    Women must be an integral part of the
             land tenure issues are often contentious, and               implementation of land programmes.
             women seeking to assert their rights may                    Training community members as paralegals,
             be subject to pressure from their families                  topographers and conflict mediators can
             and communities. The provision of legal                     help build community skills and increase the
             protections and affordable legal services                   probability that women’s concerns will be
             are vital in this respect. Mobile legal clinics             addressed.
             with staff trained in land issues may be a
             useful solution during land formalization                   Adjust bureaucratic procedures
             programmes.                                                 Simple steps such as making space for
                                                                         two names on land registration forms can
             Ensure that women’s voices are heard                        be a powerful tool for encouraging joint
             Meaningful representation constitutes an                    titling and protecting the rights of women
             important step towards helping women                        within marriage. In Brazil, for example,
             gain access to established rights. Women’s                  women were guaranteed equal rights to
             organizations can be effective in promoting                 land distributed through agrarian reform
             local participation, building a consensus and               in 1988, but few women were registered as
             raising consciousness at all levels. The role               beneficiaries because the registration forms
             played by women’s organizations is especially               mentioned them only as dependants. The
             valuable as women are generally not well                    forms were changed in 2001 to include the
             represented in decision-making bodies, and                  names of both spouses as co-applicants or
             they are often instrumental in pressuring for               beneficiaries (Deere, 2003).
             government programmes to include women                         Rural women often lack the documents
             as equal participants.                                      (such as birth records) required to obtain
               Rwanda provides an example of how state                   land titles, so facilitating access to such
             institutions and civil society organizations can            documents may be necessary. Placing
             work together to secure women’s land rights.                photographs of owners on land certificates
             Rwanda successfully reformed its inheritance                can reduce the likelihood of cheating and
             and land tenure legislation and now has                     manipulation. Ethiopia’s land programme,
             among the best legal conditions for gender                  for example, requires that certificates for
             equity in these areas. Enactment of the new                 women bear their photographs to help
             laws was made possible by the participation                 ensure that they retain control over their
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                                                                                                                                                 49
land. This measure has been credited with                         reproductive roles, which reflects social
improving their security of tenure and has                        norms and child-rearing responsibilities. As
facilitated the renting-out of land by women                      noted in Box 3 (see page 14), in most rural
(Deininger et al., 2007).                                         areas women undertake most of the work
                                                                  related to child care, food preparation
Gather sex-disaggregated data for                                 and other household responsibilities such
policy design and monitoring                                      as collecting fuel and water. Women are
Gathering sex-disaggregated data can help                         also heavily involved in unpaid agricultural
improve the design and effectiveness of                           production. When all household activities
land-titling programmes. In Cambodia, for                         are taken into account, women generally
example, a land-titling project conducted a                       work longer hours than men. Women face
social assessment before implementation,                          multiple trade-offs in the allocation of their
revealing useful insights into gender                             time and, without policies and investment in
inequality and land ownership that were                           labour-saving technologies, labour market
subsequently used to inform the programme                         participation is often not an option – even
implementation. The fact that 78 percent                          when the opportunities are available.
of new titles were issued in the joint names                      Labour-saving technologies are discussed
of husbands and wives testifies to project’s                      separately in the section on “Closing the
success in ensuring the inclusion of women.                       technology gap” (see page 56).
                                                                     Improving women’s labour market
                                                                  participation also requires that governments
Closing the gap in rural labour                                   create a good investment climate through
markets19                                                         strengthening property rights and providing
                                                                  public goods such as roads, electricity and
For most women in developing countries                            water. Women’s unequal access to assets and
labour is their key asset. Agriculture is of                      resources such as land limits their options for
particular importance as a source of self- and                    self-employment. Easier access to firewood,
wage-employment, especially for women                             water and markets relaxes women’s time
(and men) who lack training or resources                          constraints and can make an appreciable
for employment in other sectors. Viewed                           difference in their ability to participate in
in this context, agriculture also contributes                     employment and self-employment. Women
to poverty alleviation. Agricultural                              need to be involved in investment planning
growth generates demand for labour and                            right from the beginning. In Peru, for
adds upward pressure on real wages for                            example, women’s direct participation in
unskilled labour. Both of these have positive                     the design of a rural roads project ensured
implications for poor men and women, but                          that greater priority was given to their
especially so for the latter (see Chapter 3).                     needs. Upgrading was not restricted to roads
  The principle that both employment and                          connecting communities, but was extended
job quality matter is reflected in target 1B                      to many non-motorized transport tracks
of MDG 1: “Achieve full and productive                            used mostly by women and ignored by other
employment and decent work for all,                               road programmes. The resultant reduction in
including women and young people”. The                            time spent obtaining food and fuel supplies
United Nations’ “Decent Work” agenda for                          enabled women to participate more in
achieving MDG 1B promotes four objectives                         markets and fairs, and 43 percent of them
that include employment generation as                             reported earning higher incomes (World
well as social protection, enforcement of                         Bank, 2008).
labour standards and regulations, and social
dialogue.                                                         Reduce gender inequalities in human
                                                                  capital
Target women’s multiple trade-offs                                Women remain significantly overrepresented
Perhaps the gender issue that has most                            among the illiterate (UN, 2009). Improved
relevance for labour market participation                         access to education and better-quality
is that of time allocated to productive and                       education will help reduce some of the wage
                                                                  gap and, more importantly, allow women
19
     The analysis in this section draws on Termine (2010).        to diversify by widening the opportunities
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             available to them. In countries where                       part of the Ethiopian Government’s food
             agriculture is a major source of employment                 security strategy and reaches over 7 million
             for women, skill building should address                    chronically food-insecure individuals. Support
             relevant skills and knowledge gaps and focus                for pregnant and lactating women is one
             on extension services and vocational training.              important benefit for many women. At the
             A higher probability of obtaining a job in a                community level, the creation of water-
             particular sector will also influence parents’              harvesting facilities and land rehabilitation
             educational choices for their children. In                  initiatives is a positive development for
             the Philippines, women are more likely to                   both women and men. Women also gain
             obtain non-farm employment than men and                     from the programme through the change
             this partly explains the higher educational                 in men’s attitudes towards women’s work
             attainment of girls (Quisumbing, Estudillo                  capabilities as a result of regular joint work
             and Otsuka, 2003).                                          on public works. The programme has helped
               Policy interventions need to focus                        increase household food consumption and
             on school enrolment for girls, health                       contributes to the costs of providing for
             interventions such as immunization and                      children’s needs, including clothing and
             nutritional interventions that target women’s               education and health-care costs (Holmes
             specific needs throughout their life cycle.                 and Jones, 2010). These benefits have been
             Conditional transfer programmes (see                        particularly valuable in the case of female-
             Box 8, page 44), which are often targeted                   headed households who, prior to the
             at the women in the household, have been                    programme, had fewer alternative avenues
             used successfully to improve the education,                 for support.
             health and nutrition of children and women                     In India, the National Rural Employment
             (Quisumbing and Pandolfelli, 2010).                         Guarantee Act (NREGA) was implemented
                                                                         in 2005 with the goal of improving the
             Capitalize on public works programmes                       purchasing power of rural people. It
             Informal labour is a major source of income                 provides a legal guarantee for 100 days of
             for unskilled women in general, but                         employment per year for adult members of
             especially so in times of crisis. Public works              any rural household who are willing to do
             schemes can provide support to unskilled                    unskilled manual work on public projects
             workers, including women. These are public                  in return for the statutory minimum wage.
             labour-intensive infrastructure-development                 It also aims to empower rural women
             initiatives that provide cash or food-based                 by promoting their participation in the
             payments in exchange for work. Such                         workforce through a quota: at least one-
             programmes have a number of advantages:                     third of all workers who have registered and
             they provide income transfers to the poor                   requested work under the scheme in each
             and are often designed to smooth income                     state must be women. Moreover, the Act
             during “slack” or “hungry” periods of the                   stipulates the payment of equal wages for
             year; they address infrastructure shortages                 men and women. Women’s status appears
             (rural roads, irrigation, water-harvesting                  to be strengthened when they are employed
             facilities, tree plantations, facilities for                through the programme, particularly
             schools and health clinics); they are typically             when they have access to income through
             self-targeting, in view of the relatively low               their own bank accounts. NREGA’s design
             benefit levels and heavy physical labour                    incorporates the provision of crèche facilities,
             requirements (Subbarao, 2003), and thus                     intended as a means of enhancing women’s
             entail lower administrative costs than many                 participation, but the provision of child-care
             other safety-net measures. They are also                    facilities remains a serious implementation
             politically popular owing to the requirement                challenge (Jandu, 2008; Holmes and Jones,
             that beneficiaries must work (Bloom, 2009),                 2010).
             whereas generating support for direct
             cash transfers, particularly from middle-                   Strengthen women’s rights and voice
             class voters, can be more challenging (e.g.                 The lack of voice suffered by women,
             Behrman, 2007).                                             especially in rural communities, is both
               The Ethiopian Productive Safety Net                       cause and consequence of the gender
             Programme was launched in 2005 as                           differences observed in rural labour markets.
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                                                                                                                                                51
Institutional changes can help achieve
decent work opportunities and economic                           Closing the financial services gap21
and social empowerment through labour
markets and at the same time reduce                              Women’s access to financial services is
gender inequalities in the context of                            conditioned by their legal, social and
informal employment in agriculture. Public                       economic position within the community
policies and legislation can influence public                    and household. Some of the interventions
attitudes and the values that underlie                           required to close the gender gap in access
gender inequalities. Government legislation                      to financial services are similar to those
is essential for guaranteeing equitable                          needed for other asset categories. For
employment conditions that protect workers                       example, giving women equal rights to
in both formal and casual employment,                            enter into financial contracts is a crucial first
the latter being of particular relevance to                      step in countries where legal and customary
women. For example, governments can                              restrictions prevent women from opening
support the organization of women in                             savings accounts, taking loans or buying
informal jobs. At the same time, collective                      insurance policies in their own right.
bargaining and voluntary standards can be                          Microfinance programmes have been
important, in conjunction with more formal                       highly effective in overcoming the barriers
legislation. Rural producer organizations                        faced by women in accessing formal
and workers’ unions can play a vital role                        credit markets, as discussed in Chapter 3.
in negotiating fairer and safer conditions                       Considerations for improving women’s access
of employment, including better product                          to financial services are considered below.
prices and wages, and in promoting gender
equity and decent employment for men and                         Promote financial literacy
women.                                                           Financial institutions, governments and NGOs
   Nevertheless, prevailing vertical and                         should offer financial literacy training to
horizontal institutional arrangements (i.e.                      ensure that women can compare products
producer organizations, cooperatives,                            and make decisions based on a clear
workers’ unions, outgrower schemes) are                          understanding of the characteristics and
generally controlled and managed by                              conditions of the products available (Mayoux
men. There is thus a need for effective                          and Hartl, 2009). Such efforts could involve
empowerment of women among the                                   steps such as disseminating information and
membership and leadership positions                              promotion materials in places or through
in these organizations to ensure that                            channels that women can access, simplifying
rural women have a stronger voice and                            application procedures and adapting them
decision-making power.20 At the same                             to women’s literacy and numeracy levels,
time, it is necessary to promote gender                          and simplifying insurance contracts and
sensitivity within representative bodies                         communicating their conditions using
through the training of men and women                            language and examples that less-literate
representatives, as this does not derive                         women can easily understand.
automatically from women’s participation.
Women representatives do not always have                         Design products that meet the needs of
the capacity to address issues in a gender-                      women
sensitive way, especially when gender roles                      The past few years have seen noticeable
are perceived as rigid or if there exists strong                 progress in extending insurance products
opposition or conflict with men’s interest.                      to small producers and to rural areas. Crop
Gender sensitivity training is also relevant for
staff in institutions that work with women
and implement gender-focused policies.
                                                                 21
                                                                   The material in this section is based on Fletschner and
                                                                 Kenney (2010). Important studies in this field include
                                                                 Berger (1989), Goetz and Gupta (1996), Pitt and Khandker
                                                                 (1998), Hashemi, Schuler and Riley (1996), Baydas, Meyer
                                                                 and Alfred (1994), Fletschner (2009), Fletschner and Carter
                                                                 (2008), Ashraf, Karlan and Yin (2010, Pitt, Khandker and
20
  Additional information on women’s parliamentary                Cartwright (2006), Holvoet (2004), Hazarika and Guha-
representation is available at the website of the Inter-         Khasnobis (2008), Besley (1995), Boucher, Carter and
Parliamentary Union website (www.ipu.org).                       Guirkinger (2008) and World Bank (2007a).
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             insurance and livestock insurance, for                              into a major income shock for resource-poor
             instance, are increasingly being offered as                         households, and women may be particularly
             safety nets to farmers. Generally, however,                         vulnerable because they are more likely to be
             such products are designed without due                              assigned the role of caregiver. Illness in the
             attention to gender differences, and the                            family thus reduces women’s ability to engage
             degree to which women access them is                                in income-generating activities and weakens
             unclear. A notable exception to this pattern                        their ability to influence family decisions.
             is the approach taken by BASIX, a large                               Life events such as birth, death, marriage
             microfinance institution in India that offers                       and other cultural ceremonies also constitute
             weather insurance to women’s self-help                              shocks to rural households. Most micro-
             group members in drought-prone areas                                insurance plans described here cover
             (Fletschner and Kenney, 2010).                                      pregnancy and birth-related expenses. Some
                A number of multilateral financial                               offer life and funeral insurance (Sriram, 2005;
             institutions and NGOs offer health insurance                        Mgobo, 2008), but informal safety nets, such
             to women (Table 2). Illness can translate                           as burial societies, remain important sources

              TABLE 2
              Selected examples of health insurance products targeted towards women
                        Provider
                                                            Beneficiaries                                    Details
                      and country

              Bangladesh Rural                      Originally BRAC members           Year started: 2001
              Advancement Committee                 only; since 2007 open to all      Members: 10 000 (as of 2004) (Matin, Imam and
              (BRAC)                                community members (poor           Ahmed, 2005)
              Bangladesh                            rural women are policy-           Results: 55 percent did not renew after first year;
                                                    holders)                          poorer households less likely to know about
                                                                                      programme and better-off households more likely
                                                                                      to enrol; some clients found it difficult to pay
                                                                                      annual premium; others who did not use services
                                                                                      but enrolled found it to be a “waste” (ibid.)

              SKS                                   SKS borrowers, who are            Year started: 2007, expanded in 2009 to cover
              Bangladesh                            primarily women (spouse and       spouses (usually husbands)
                                                    up to two children covered)       Members: 210 000 (as of 2008); required for all
                                                                                      new borrowers or renewing borrowers (as of 2007)
                                                                                      (Chen, Comfort and Bau, 2008)
                                                                                      Results: Women aged 16–30 are heaviest users (ibid.)

              Self Employed Women’s                 SEWA members and non-             Year started: 1992
              Association (SEWA)                    members (women are policy-        Members: 110 000 (as of 2003), two-thirds from
              India                                 holders)                          rural areas (Ranson et al., 2006)
                                                                                      Results: Found to reduce clients’ vulnerability to
                                                                                      shocks overall, but slow processing costly to clients;
                                                                                      initially coverage was mandatory for all borrowers,
                                                                                      but once it became voluntary, 80 percent dropped
                                                                                      coverage (McCord, 2001)

              SPANDANA                              Borrowers (compulsory, as         Year started: 2003 (Sriram, 2005)
              India                                 part of loan product)             Members: 84 000, including spouses (as of 2004)
                                                    (Sriram, 2005; CGAP, 2004)        (CGAP, 2004). In 2007, 96.5 percent of borrowers
                                                                                      were women (Mix Market, 2010)

              Port Sudan Association                Women NGO members                 Year started: 2007 (Mayoux and Hartl, 2009)
              for Small Enterprise                  (individual low-cost access to    Number of members: unknown
              Development (PASED)                   state health insurance)
              / Learning for                        (Mayoux and Hartl, 2009)
              Empowerment Against
              Poverty
              (LEAP)
              Sudan

              Kenya Women Finance                   Medium and low-income             Year started: 2008
              Trust Limited (KWFT)                  women, with option to cover       Members: unknown, potentially 100 000 (total
              Kenya                                 family members                    KWFT members) (Mgobo, 2008)

              Zurich Financial Services             WWB affiliates (women             Year started: 2009
              and Women’s World                     member MFIs)                      Members: not yet known, but WWB network has
              Banking (WWB)                                                           21 million members (WWB, 2010)
              (Global)
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of income-smoothing for rural households,            reducing the need to travel long distances,
especially for women, who may face the loss          allowing them to sidestep social constraints
of all assets upon a husband’s death (Dercon         that restrict women’s mobility or the people
et al., 2007; Mapetla, Matobo and Setoi,             with whom they can interact (Duncombe
2007).                                               and Boateng, 2009). In another example, a
                                                     bank in Malawi that hosts small-scale savings
Promote a women-friendly and                         has introduced innovations that give women
empowering culture                                   greater control over their income, such as
Lenders and other financial institutions             the use of a biometric card that allows only
should promote a gender-sensitive culture            the card holder to withdraw money from the
throughout their organization (World                 account and the facility to open an account
Bank, FAO and IFAD, 2009). Women should              without an identity card, which many people
be consulted and included in discussions,            in rural areas do not possess. The bank has
decision-making, planning and provision of           successfully attracted large numbers of
services. Marketing strategies, promotion            women to open bank accounts (Cheston 2007,
and service delivery should be gender-               cited in Quisumbing and Pandolfelli, 2010).
sensitive. Bringing men into projects and               Financial institutions in countries such as
groups can have positive effects on gender           Brazil, India, Kenya, the Philippines and South
relations and improve the success of the             Africa have been able to reach rural customers
project, but also risks losing the focus on          at a lower cost by handling transactions
women (Armendáriz and Roome, 2008).                  through post offices, petrol stations and
  A large body of evidence shows that                stores, and many telecommunication service
lending to women helps households diversify          providers allow their customers to make
and raise incomes and is associated with             payments or transfer funds (World Bank,
other benefits such as increased livelihood          2007a). These more accessible outlets can be
diversification, greater labour market               particularly beneficial for rural women who
participation, more education and better             have difficulty travelling to central business
health. It does not necessarily empower              locations.
women, however, if they do not control the
assets that are built or increased (Garikipati,
2008).                                               Closing the gap in social capital
  Products designed to strengthen women’s            through women’s groups
position include the Grameen Bank’s loans
for purchasing land or houses requiring              Building women’s social capital can be
that they be registered in women’s names             an effective way to improve information
and the loans offered by Credit and Savings          exchange and resource distribution, to pool
Household Enterprise in India for parents to         risks and to ensure that women’s voices
buy assets for their daughters, enabling them        are heard in decision-making at all levels.
to generate income, delay their marriage             Community-based organizations, including
and have assets they can take with them              women’s groups, can be an effective means
when they marry (Mayoux and Hartl, 2009).            of generating social capital. Functioning as
Along similar lines, a host of products have         production cooperatives, savings associations
been designed to benefit other women in              and marketing groups, women’s groups
the community indirectly (Mayoux and Hartl,          can promote production and help women
2009): for instance, loans for businesses that       maintain control over the additional income
employ women, or for businesses that offer           they earn, as has been demonstrated by
services such as child care that benefit other       a project based around polyculture fish
women.                                               production in Bangladesh. As the project
                                                     proved successful in providing additional
Use technology and innovative delivery               incomes, the position of women within
channels                                             the household and community was also
Technological innovations such as prepaid            strengthened (Naved, 2000).
cards and mobile phone plans to make loan               Achieving scale through pooling resources
payments and transfer cash make it easier            can help women overcome some of the
for women to gain access to capital by               constraints faced by individual farmers.
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             In Kenya, women farmers pooled their                        and Jiggins, 2002). Women-only groups can
             land parcels and organized themselves to                    be an effective stepping stone to graduating
             establish savings associations and to deal                  into mixed-sex organizations or joining
             with stockists and traders. In this way, they               established groups.
             were able to solve problems experienced                       Self-help groups have also proved to be
             in acquiring access to land, credit and                     an effective method for connecting women
             information (Spring, 2000). An impressive                   with financial institutions. Such groups may
             example of achieving scale is the Self                      operate at the village level and typically
             Employed Women’s Association (SEWA),                        require their members to meet regularly.
             which was founded in 1972 in Ahmedabad,                     Savings are collected from each member and
             India. This started as a small membership                   either deposited in rural banks or loaned
             organization for poor women working in                      to other group members. After a group has
             the informal sector. Today, it has more than                demonstrated its capacity to repay loans,
             one million members in 14 districts across                  rural banks typically leverage the group’s
             India and aims at organizing groups with                    savings and provide additional capital that
             regard to services, access to markets and                   group members may use for agricultural
             fair treatment. Its largest cooperative is                  purposes (World Bank, FAO and IFAD, 2009).
             the SEWA Bank, which in 2007–08 had over                    There is evidence that working through
             300 000 accounts with about US$16.6 million                 groups can help women retain control over
             in deposits (see Box 10). Established                       the loans they receive and enhance the
             associations and networks are not always                    returns to investments in women-managed
             accessible to women, as demonstrated by                     enterprises (Garikipati, 2008).
             another example, from southwest China.                        While groups can be an important way
             Here women found it difficult to access the                 of increasing women’s voice, there can
             male-dominated system of networks relating                  sometimes be an over-reliance on this
             to the formal plant-breeding system (Song                   mechanism. Women’s groups, like any


                BOX 10
                India’s Self Employed Women’s Association (SEWA)


                The main goal of the Self Employed                       leaders. The low literacy levels of female
                Women’s Association (SEWA) is to                         participants are a major challenge to
                organize women to achieve full                           effective training delivery. SEWA also
                employment and self-reliance. In order to                offers functional literacy training that
                achieve this, SEWA sets up small self-help               is group-based and facilitated by a local
                groups that meet monthly in members’                     trainer from the community. The training
                fields, homes or community rooms.                        focuses on reading skills and is designed
                Farmers choose to join these groups to                   around women’s specific needs.
                share mutual interests and concerns and                     SEWA’s village resource centres help
                to solve their problems collectively. For                farmers, through the self-help groups,
                example, in the Sabarkantha district of                  to identify the potential benefits
                Gujarat State, SEWA supported small-scale                of new technologies, evaluate their
                women farmers in creating a federation,                  appropriateness and participate in
                the Sabarkantha Women Farmer’s                           technology development processes. The
                Association, and conducted a watershed                   resource centres also provide farmers with
                conservation campaign in seven villages.                 good-quality inputs, market information
                   SEWA’s facilitation approach includes                 and technical advice. SEWA’s cooperatives
                capacity building provided by professional               are authorized seed distributors of the
                organizations. These organizations                       Gujarat State Seed Corporation and
                train SEWA members in managerial and                     provide timely and reasonably priced
                leadership skills, providing training for                quality seeds (up to 20 percent below
                self-organization and collective action                  local market prices). The village resource
                to assist members in becoming confident                  centres communicate current output
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collective action process, face challenges           clearly the specific issue they are trying to
and costs. Membership fees may exclude               address in group formation, and that using
resource-poor women from joining, and                existing, sometimes informal, groups and
membership criteria such as land ownership           networks has proved more successful than
would bar landless women from becoming               initiating them from scratch.
members. Timing and length of meetings                  Mixed-sex groups can be more effective
may interfere with women’s daily tasks.              where joint action is required, such as in
Building trust within newly formed groups            natural resource management (Pandolfelli,
can take a significant amount of time.               Meinzen-Dick and Dohrn, 2008). In order for
Women may also not be interested in                  women to participate actively in mixed-sex
joining a group because the group does not           groups, the groups must address women’s
address their main concerns. Quisumbing              problems and should be set up to allow the
and Pandolfelli (2008) report results from a         participation of more than one member of a
project in the Philippines that encouraged           household, if required (Meinzen-Dick et al.,
women to monitor a lake to assess whether            2010). Mixed groups should also allow for
or not soil conservation techniques reduced          women’s voices to be heard. A case study
silting. Women’s participation was low,              on Ethiopia found that meetings with only
however, because their main interest was in          women or with an equal number of men
health issues. When the project started to           and women increased women’s willingness
emphasize the relationship between health            to voice their opinion (German and Taye
and water quality, women’s participation             2008). The specifics of group mechanisms,
increased. Understanding the motivations             such as the management of funds and
for joining a group is therefore essential in        sharing of benefits, and the share of women
ensuring group sustainability (Pandolfelli,          in leadership positions, will also play a
Meinzen-Dick and Dohrn, 2008). Policy-               significant role in encouraging women to
makers and practitioners need to understand          participate.




  prices to female leaders in each village           well as their communication facilities such
  cluster through regular SMS messages,              as the SEWA radio station. The SEWA
  thereby enabling the self-help groups              approach is accountable and inclusive
  to bargain for better prices for their             owing to its grassroots foundations and
  produce.                                           the effectiveness of service provision
     Among the SEWA organizations that               through self-help groups. SEWA is
  enable market access for small-scale               also powerful because of its internal
  farmers, the Rural Distribution Network            cohesiveness and its linkages with external
  (RUDI) plays a special role. RUDI acts as a        partners such as government departments,
  link between farmers and consumers by              universities, research and development
  making regularly used goods available              agencies, NGOs and private companies.
  to villagers. Grains, spices and salt                The 2 140 SEWA self-help groups
  from various districts are transported             often radically improve women’s lives by
  to a processing centre and dispatched              increasing their income and food security
  to selling centres. In this way, RUDI              and by enabling them to seize new
  provides an outlet to farmer groups and            opportunities. For example, the creation
  employment to saleswomen.                          of the Sabarkantha Women Farmer’s
     SEWA’s approach is particularly                 Cooperative enabled women farmers to
  successful because it is an integrated             reclaim 3 000 hectares of ravine lands in
  process. Self-help groups and SEWA are             73 villages. Incomes increased from an
  closely linked through SEWA institutions           average of 5 000 Indian rupees (about
  such as their microfinance and insurance           US$ 112 ) to as much as 15 000 Indian
  agencies and their training facilities, as         rupees a year.
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                The ability to organize mixed-sex groups                 could be made much less onerous and time-
             will depend on the gender segregation                       consuming through the adoption of simple
             within a community. In communities with a                   technologies.
             high level of gender segregation, single-sex                   Water is of particular importance to
             groups may lead to more desirable outcomes                  rural households because it is necessary
             for women (Pandolfelli, Meinzen-Dick and                    for agricultural and household chores,
             Dohrn, 2008). Sometimes, however, excluding                 but men and women often have different
             men can generate unnecessary obstacles.                     priorities with regard to water use. Women
             A project introducing the new livelihood                    are frequently responsible for collecting all
             strategy of mud-crab production to supply                   water used domestically, i.e. drinking water,
             hotels in Unguja Island, United Republic of                 sanitation and health. The introduction of
             Tanzania, excluded men and the resultant                    water sources in villages can significantly
             anger among the men added transaction and                   reduce the time spent by women and girls
             input costs as women had to rely on a small                 fetching water (IFAD, 2007). For example,
             number of male fishers for seedstock and                    the construction and rehabilitation of water
             feedstuff (Coles and Mitchell, 2010). Projects              sources in six rural provinces of Morocco
             that intervene within the local socio-cultural              reduced the time that women and young
             dynamics should avoid “default” options                     girls spent fetching water by 50–90 percent.
             and, instead, base their interventions on the               Primary school attendance for girls in these
             specific context and the underlying problem.                provinces rose by 20 percent over a period of
                                                                         four years, which was partly attributed to the
                                                                         fact that girls spent less time fetching water
             Closing the technology gap                                  (World Bank, 2003).
                                                                            Water projects that meet multiple
             Closing the gap in women’s access to a                      livelihood objectives and take gender issues
             broad range of technologies could help free                 properly into account are more likely to be
             their time for more productive activities,                  sustainable (Quisumbing and Pandolfelli,
             enhancing their agricultural productivity,                  2010). In Manzvire village, Zimbabwe, for
             improving the market returns they receive                   example, a borehole rehabilitation project
             and empowering them to make choices that                    involved men and women in the decision-
             are better for themselves and their families.               making process regarding the appropriate
             Closing the technology gap requires that                    technology and sites for new water points,
             the necessary technologies exist to meet                    and women were trained in maintaining the
             the priority needs of female farmers, that                  new water sources. Their active involvement
             women are aware of their usefulness, and                    provided women with a strong sense of
             that they have the means to acquire them.                   ownership for the sources; for example, they
                                                                         established saving schemes that provided
             Develop technologies and environments                       funds to buy spare parts. One of the project’s
             that address women’s needs                                  results was that four times more boreholes
             Previous chapters documented that rural                     than targeted were rehabilitated (Katsi,
             women work very long days balancing a                       2006).
             variety of tasks related to crop and livestock                 Firewood collection for cooking purposes
             production, wage employment, child care                     can also occupy a large share of women’s
             and additional household obligations.                       time and is – quite literally – a heavy burden.
             The latter, such as food preparation and                    Women in rural Senegal, for example,
             collecting firewood and water, occupy a                     walk several kilometres a day carrying
             large amount of women’s time and limit                      loads of over 20 kg of wood (Seck, 2007).
             women’s participation in more productive                    Deforestation and unfavourable weather
             activities. Studies from Kenya, Uganda                      events, such as drought, can increase
             and the United Republic of Tanzania, for                    the time spent on firewood collection.
             example, show that children and women                       Fuel-efficient stoves can reduce firewood
             in rural areas fetch water from the main                    requirements by 40–60 percent (FAO, 2006b),
             water source on average four times per day                  in addition to reducing indoor pollution
             and require about 25 minutes for each trip                  and the time required for cooking. Locally
             (Thompson et al., 2001). Many of these tasks                manufactured stoves can also provide
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                                                                                                                                  57
income-earning opportunities for rural             access to them. Conducting baseline surveys
artisans. In western Kenya, for example,           of households and communities before new
the introduction of the Upesi stove led to         technologies are introduced may help predict
considerable reductions in smoke levels.           how men and women will be affected
Women who used the stove reported time-            by them (Quisumbing and Pandolfelli,
savings of about ten hours per month.              2010). Greater involvement of women in
The stove saves up to 40 percent of fuel           agricultural research and higher education
compared with traditional three-stone              could also enhance the development of
fires and has a lifespan of about four             female-friendly technology.
years. Upesi stoves are produced by local             Improved crops with higher yields and
women’s groups, generating income-earning          better adapted to pests and diseases can
opportunities for rural women (Okello,             also be labour-saving, by reducing the time
2005). Woodlots, agroforestry and improved         for cropping operations. Certain crops, for
fallows can further reduce the time spent in       example cassava and other root and tuber
collecting firewood by bringing the sources        crops, have lower labour requirements
of firewood closer to the home. These              and allow for more flexibility in cropping
measures require secure tenure as well as          operations. Varieties that are harvested
labour inputs and investments for which            in seasons with low labour requirements
benefits will only be realized after a number      can ease labour bottlenecks. Integrated
of years (FAO, 2006b).                             pest management techniques can decrease
   Appropriate farm tools for women can            labour requirements and costs for pesticide
also reduce drudgery and time spent in the         application, reduce farmer exposure to
field. Farm tools that are predominantly           hazardous chemicals and increase yields.
used in operations dominated by women,             Conservation agriculture, or no-tillage
for example weeding or post-harvest                systems, decreases the labour needed for
activities, are often not gender-specific. In      land preparation and weeding, because the
fact, technology developers often think of         field is covered with cover crops and seeding
technologies as being gender-neutral, but on       is done directly without preparing the
average women tend to be of lower weight           seedbed (FAO, 2006b). Biological nitrogen-
and height compared with men and may not           fixation technologies to improve soil fertility,
have equal muscular strength (Singh, Puna Ji       such as agroforestry innovations or grain
Gite and Agarwal, 2006). Improved farming          legumes, can raise productivity and save
tools can facilitate seed-bed preparation,         labour.
planting, weeding and harvesting activities.
For example, a case study in Burkina Faso,         Improve extension services
Senegal, Uganda, Zambia and Zimbabwe               Extension services are important for
showed that long-handle hoes could ease the        diffusing technology and good practices,
burden of the work for women compared              but reaching female farmers requires careful
with traditional short-handle hoes, but            consideration. In some contexts, but not all,
they were not acceptable in some of the            it is culturally more acceptable for female
countries because standing up was associated       farmers to interact with female extension
with laziness (IFAD/FAO/FARMESA, 1998).            agents. Whether they are male or female,
Another study from India demonstrated that         extension agents must be sensitive to the
women who used a groundnut decorticator            needs and constraints faced by their female
were able to decorticate about 14 times            clients. Extension services for women must
more groundnuts and used significantly less        consider all the roles of women; women’s
physical effort than women who decorticated        needs as farmers are often neglected in
groundnuts by hand. When preparing land            favour of programmes aimed at household
with a new hand tool designed for making           responsibilities.
ridges for vegetable crops, women were able           Hiring female extension agents can be
to double the number of rows finished in           an effective means of reaching female
one hour (Singh, Puna Ji Gite and Agarwal,         farmers. The United Republic of Tanzania,
2006). Thus, attention should be paid to           for example, raised the share of female
developing appropriate, context-specific           extension agents to 30 percent in the
technologies as well as enhancing women’s          mid-1990s, because many female farmers
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             indicated that “they felt freer to discuss                  23 percent higher increases in income from
             problems with them ... and their time                       livestock production than participants from
             preferences were better met” (Due,                          male-headed households and were able to
             Magayane and Temu, 1997). This preference                   nearly double per capita agricultural income.
             is not universal, however, so in many cases                 FFS were easily accessible to women as well
             properly trained male extension agents may                  as to poor farmers and farmers with low
             be able to provide equally effective services.              literacy levels. Farmers particularly valued
                Male extension agents must be sensitized                 the participatory learning approach and the
             to the realities of rural women and the                     ability to do practical experiments using new
             quality of information provided to women                    technologies in the field (Davis et al., 2009).
             improved. This requires careful and location-                  When targeting female participation in
             specific analysis of their situation. Cultural              the FFS, time constraints play a significant
             barriers could be overcome by organizing                    role. A case study of FFS for integrated pest
             women in groups and possibly providing                      management in rice in Sri Lanka showed that
             separate training for male and female                       they can take up to 15 half-day meetings in a
             farmers. Extension systems will also have                   single season (Tripp, Wijeratne and Piyadasa,
             to be more innovative and flexible to                       2005). Crop preferences or crop operations
             account for time and mobility constraints.                  relevant to women farmers also determine
             Indeed, women farmers tend to be less                       the extent to which women participate. A
             mobile than their male counterparts owing                   participatory potato research initiative in
             to time constraints, restricted access to                   Peru attracted only about 12 percent female
             transportation and potential social and                     participation because women thought
             cultural obstacles that keep them from                      of potato as a “male” crop. However,
             travelling outside their village boundaries.                participation was as high as 60 percent in
             Women also often have seasonal workloads                    sessions dealing with planting, harvesting
             that can conflict with the timing of extension              and evaluating potato clones because these
             training programmes.                                        tasks were perceived as “female” (Buck,
                The Government of Ethiopia has                           2001; Vasquez-Caicedo et al., 2001).
             endeavoured to render its extension services                   FFS are sometimes criticized as being
             more gender-responsive by mandating its                     financially unsustainable because they
             national and regional Bureaus of Agriculture                require high initial investments and
             to introduce extension services closely linked              significant recurrent costs. Comparisons
             to women’s activities, to encourage women                   show that costs vary widely by country and
             to participate in every programme and to                    crop, and that costs per farmer decline as
             assist women in obtaining better access to                  project managers learn to use local training
             agricultural inputs (Buchy and Basaznew,                    materials, replace international experts
             2005). Women’s involvement in farmer-to-                    with local staff, and increase the number
             farmer training and extension has also had                  of participants (van den Berg and Jiggins,
             positive results in Uganda (Box 11).                        2007). In order to increase the impact of FFS
                                                                         on women and to ensure their sustainability,
             Scale up farmer field schools                               it is important to train women farmers
             Farmer field schools (FFS) have proved to                   in effectively communicating learned
             be a participatory and effective way of                     experiences. This will enable them to become
             empowering and transferring knowledge                       facilitators in other FFS or to communicate
             to women farmers. For example, women                        with non-participating farmers.
             in Kenya, Uganda and the United Republic
             of Tanzania who participated in FFS were
             more likely to adopt major technologies,                    Key messages
             including improved crop varieties, livestock
             management and pest control techniques.                       •	 Gender gaps can be closed across a wide
             In all three countries, women made up, on                        range of agricultural inputs, assets and
             average, 50 percent of all FFS participants                      services. Many steps are required by
             and they benefited significantly from their                      many different actors – governments,
             participation. For example, participants                         civil society, the private sector and
             from female-headed households achieved                           individuals – but the basic principles are
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BOX 11
Women in a sustainable rural livelihoods programme in Uganda1


Women feature prominently in a                    trainers are women: about 58 percent
sustainable rural livelihoods (SRL)               of community-based rural development
programme established in 2004 in eastern          extension workers, 75 percent of
Uganda’s Kamuli District. The primary             community nutrition and health workers,
goals of the programme are to improve             76 percent of committee members and
food security, nutrition and health at            71 percent of executive committee
the household and community levels.               members.
Related goals are increased sources and             In response to the training and support
levels of income, resilience to stresses and      that they receive, the rural development
shocks, and the sustainable management            extension and community nutrition and
of natural resources. The SRL is a                health workers provide training and
collaborative programme of Iowa State             outreach to farmer group members and
University’s Center for Sustainable Rural         others in their communities and well
Livelihoods, Makerere University’s Faculty        beyond. More than 2 000 other households
of Agriculture and VEDCO (Volunteer               have benefited from training and outreach
Efforts for Development Concerns), a              services provided by these workers.
Ugandan NGO.                                        As a result of their participation in this
   The programme employs a farmer-to-             programme, women’s human capital has
farmer training and extension approach to         been enhanced through training and
demonstrate and disseminate information           through experience gained in developing
on key management practices, for                  leadership skills, improved nutrition and
example: planting banana or cassava               health, and community-wide respect
in ways that ensure productivity and              for their role as sources of valuable
control diseases, enhancing soil fertility        knowledge. In terms of social capital, they
through composting with manure,                   are integrally involved in farm groups and
growing and utilizing nutrient-dense              emerging marketing associations. Another
crops such as amaranth grain and Vitamin          key result has been a significant increase in
A-rich sweet potatoes. It also emphasizes         household food security.
the establishment of multiplication                 Innovations made through this three-
gardens and seed nurseries, post-harvest          way partnership in Kamuli District are
management and storage, improving                 now being mainstreamed in VEDCO’s
livestock breeding and feeding, integrating       rural development support programme
nutrition and health with agriculture, farm       activities in nine other districts – for 25 000
enterprise development, marketing, and            smallholder farmers.
strengthening farmer groups.
   Groups were formed following
community meetings and were often
based on existing self-help groups such as
                                                  1
                                                   Prepared by Robert Mazur, Professor of Sociology
                                                  and Associate Director for Socioeconomic
savings clubs. A large proportion of the          Development in the Center for Sustainable Rural
1 200 farm group members, leaders and             Livelihoods, Iowa State University, USA.



   the same across the board: eliminate                  government officials and community
   discrimination under the law, make                    leaders and holding them accountable
   gender-aware policy and programming                   for upholding the law and empowering
   decisions, and give women greater voice               women to ensure that they are aware of
   in decision-making at all levels.                     their rights and able to claim them.
•	 Closing the gap in access to land and              •	 Women’s participation in rural labour
   other agricultural assets requires,                   markets requires freeing women’s time
   among other things, reforming laws                    through labour-saving technologies
   to guarantee equal rights, educating                  and the provision of public services,
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                   raising women’s human capital through                    research and technology development
                   education, eliminating discriminatory                    programmes, the provision of gender-
                   employment practices, and capitalizing                   sensitive extension services and the
                   on public works programmes.                              scaling up of FFS.
                •	 Closing the gap in financial services                 •	 Women’s groups and other forms of
                   requires legal and institutional reforms                 collective action can be an effective
                   to meet the needs and constraints of                     means of building social capital and
                   women and efforts to enhance their                       addressing gender gaps in other areas
                   financial literacy. Innovative delivery                  as well, through reducing transactions
                   channels and social networks can reduce                  costs, pooling risks, developing skills and
                   costs and make financial services more                   building confidence. Women’s groups
                   readily available to rural women.                        can be a stepping stone to closing the
                •	 Improving women’s access to agricultural                 gender gap in participation in other civil
                   technologies can be facilitated                          society organizations and government
                   through participatory gender-inclusive                   bodies.
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6. 	Closing the gender gap
    for development


Evidence from an extensive body of                          implementing provisions and policies
social and economic research surveyed                       on gender equality. Governments and
in this report confirms the contributions                   civil society must work together to
women make to the agriculture sector                        ensure that women are aware of their
and rural enterprises, the gender-specific                  rights and have the support of their
constraints they face in accessing resources                governments, communities and families
and opportunities, the potential benefits                   in claiming their rights.
for the sector and society that could be                 •	 Strengthen rural institutions and make
achieved by reducing those constraints, and                 them gender-aware. Strong, effective
lessons learned from policies, programmes                   and inclusive rural institutions are
and interventions aimed at closing the                      essential for poverty reduction, economic
gender gap in agriculture. The conclusions                  development and the empowerment
are clear: (i) gender equality is good for                  of small producers and the rural poor,
agriculture, food security and society; and                 particularly women. Efforts are required
(ii) governments, civil society, the private                to ensure that women and men are
sector and individuals, working together, can               equally served by rural institutions
support gender equality in agriculture and                  such as producers’ organizations,
rural areas.                                                labour unions, trade groups, and other
   Enabling women to achieve their                          membership-based organizations. Other
productive potential requires many of the                   public and private service providers that
same reforms that are necessary to address                  operate in rural areas, such as extension
constraints facing small-scale farmers and                  services, animal health services and
rural people in general, but additional care                microfinance organizations, should
must be taken to ensure that women’s voices                 consider the specific needs of men and
are heard in the design and implementation                  women to ensure that their activities are
of policies and interventions. No simple                    gender-aware. Women’s groups have an
“blueprint” exists for achieving gender                     important role to play, but other rural
equality in agriculture, but some principles                institutions must also be accessible to
are universal and many lessons can                          women and responsive to their needs.
be learned about best practices. Basic                   •	 Free women for more rewarding and
principles for achieving gender equality and                productive activities. The most valuable
empowering women in agriculture include                     asset most poor people have is their own
the following:                                              labour, but many women are compelled
   •	 Eliminate discrimination against women                to spend too much of their time in
      under the law. Governments have a                     drudgery: fetching water, carrying
      fundamental responsibility to ensure                  wood, and processing food by hand.
      that their laws and policies guarantee                Such work has to be done because water
      equal rights for men and women to                     pumps, modern fuel sources and grain
      control assets such as land and to receive            mills are missing. Investments in basic
      services such as education, extension                 infrastructure for essential public services
      and credit. Governments also have a                   can liberate women from this drudgery
      responsibility to ensure that institutions            and free them for more rewarding and
      and officials at all levels are fully                 productive work.
      supportive of the realization of equality          •	 Build the human capital of women
      under the law. Officials must understand              and girls. No single intervention can by
      the law and be held accountable for                   itself address the multiple challenges
62   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                   enumerated in this report, but building                  used to ensure that the resulting data
                   the human capital of women and girls                     accurately highlight gender interactions
                   is fundamental. General education and                    and inequalities in the agriculture
                   the ongoing transfer of information and                  sector. More detailed time-use surveys
                   practical skills will broaden the range of               would lead to greater understanding
                   choices women can make and give them                     of women’s contributions to household
                   more influence within their households                   production and welfare as well as to
                   and communities. Building women’s                        their time constraints. The quantity and
                   human capital makes them better                          quality of sex-disaggregated data for
                   farmers, more productive workers, better                 policy-making can be increased through
                   mothers and stronger citizens.                           the integration of agricultural censuses
                •	 Bundle interventions. Some assets are                    and surveys and the retabulation of
                   complementary and the constraints                        existing census data. Gender differences
                   women face are often mutually                            and their implications may be more
                   reinforcing. Interventions therefore                     visible when sex-disaggregated data are
                   should be appropriately bundled and                      collected, analysed and presented at
                   sequenced and should consider women                      subnational levels and by age groups.
                   within their broader social contexts.                 •	 Make gender-aware agricultural policy
                   Relaxing one constraint may be helpful,                  decisions. Virtually any agricultural
                   but others may soon become binding, so                   policy related to natural resources,
                   it is often necessary to address multiple                technology, infrastructure or markets
                   constraints. What is more, it is impossible              will affect men and women differently
                   to separate women’s economic activities                  because they play different roles
                   from their household and community                       and experience different constraints
                   roles and responsibilities. The gender-                  and opportunities in the sector.
                   related constraints women face due                       Good agricultural policy requires an
                   to power relations within the family                     understanding of the gender dimensions
                   and community may affect their ability                   at stake. Because some agricultural
                   to engage in economic activities and                     and gender issues are location-specific,
                   retain control over the assets they                      these may best be addressed through
                   obtain. Bringing men into the process                    location-specific assessments and
                   will help ensure that progress towards                   tailored policies and programmes.
                   gender equality is broadly beneficial and                Because interventions may have gender-
                   sustainable.                                             impacts that are difficult to predict,
                •	 Improve the collection and analysis of                   policies and programmes should include
                   sex-disaggregated data.22 Understanding                  the collection of baseline data and
                   of many gender issues in agriculture                     rigorous monitoring and evaluation,
                   – including crop, livestock, fisheries                   and practitioners should be prepared to
                   and forestry sectors – is hindered by                    reformulate their activities in response
                   the lack of sex-disaggregated data,                      to unforeseen developments. Making
                   and inadequate analysis of the data                      women’s voices heard at all levels in
                   that exist. Agricultural censuses should                 decision-making is crucial in this regard.
                   focus more attention on areas in which
                   women are relatively more active and
                   collect sex-disaggregated data on
                   ownership of, access to and control
                   over productive resources such as land,
                   water, equipment, inputs, information
                   and credit. They should avoid gender
                   biases in the concepts and definitions


             22	
                 FAO has developed the Agri-Gender Statistics Toolkit
             FAO, 2010i), providing technical guidance to support
             the enhanced production and use of sex-disaggregated
             agricultural data.
Part II
    World food and
agriculture in review
Part II
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                               65
World food and agriculture in review



From 2007 to 2009, a food price crisis
followed by the financial crisis and global                 Trends in undernourishment24
economic recession pushed the number of                     With the improved prospects for the global
hungry and undernourished people in the                     economy and lower food commodity
world to unprecedented levels, reaching                     prices, FAO projects that the number of
a peak in 2009 of more than 1 billion.23 In                 undernourished people in the world will
the first half of 2010, world agricultural                  decline in 2010 to 925 million people, from
commodity markets appeared to enter                         the estimated 2009 peak of 1.023 billion
calmer times. Prices of food and agricultural               (Figure 17). Despite this welcome
commodities remained high, but had                          reduction in world hunger, the number of
nevertheless declined from the peaks of                     undernourished remains unacceptably high,
2008, and the world economy was emerging                    representing the second-highest number
from recession.                                             since FAO’s records began.25
  However, there are growing concerns                          The decline in 2010 constitutes a reversal
about high market volatility. These were                    of the constant upward trend observed
reinforced from June through October                        since 1995–97. Indeed, after a steady, albeit
2010, when cereal prices – particularly                     slow, decline from 1970–71 to 1995–97, the
those of wheat and maize – increased as                     following years saw a gradual increase in
drought in the Russian Federation and high                  the number of undernourished people in
temperatures and excess rain in the United                  the world. The upward trend accelerated
States of America reduced supplies. During                  sharply in 2008 during the food price crisis.
the food price crisis, many governments                     The number of undernourished spiked in
took a number of uncoordinated policy                       2009 as a result of the financial crisis and
actions intended to ensure adequate                         the persistence of high food prices in the
supplies on domestic markets, inter alia                    domestic markets of many countries in
through export bans and other restrictions                  developing regions.
on exports. Many of these actions, in fact,                    In spite of the increase in the absolute
exacerbated price volatility on international               number of undernourished people between
markets.                                                    1995–97 and 2009, the proportion of the
  This part of the report examines levels and               population who are undernourished in the
trends in global hunger in the context of                   developing world26 continued to decline,
recent developments in agricultural markets                 albeit very slowly, even after 1995–97, before
and the global economy. It reviews recent                   increasing in both 2008 and 2009 (Figure 18).
trends in global production, consumption                    In 2010, 16 percent of the population in
and trade of food and agricultural products                 developing countries were undernourished,
and discusses price developments on                         down from 18 percent in 2009 but still well
international and domestic food markets.                    above the target set by the Millennium
The analysis focuses on increasing disquiet                 Development Goal 1C to halve to 10 percent
over price volatility and the resilience of                 the proportion of undernourished between
markets to price and economic fluctuations.                 1990 and 2015.




23	
    This review of world food and agriculture is based on   24	
                                                                A more detailed analysis of trends in global
information available at the end of October 2010. More      undernourishment and the impact of the crisis on global
current information on agricultural markets and the         food security can be found in FAO, 2010g.
world food situation can be found at http://www.fao.org/    25	
                                                                FAO estimates date back to 1969–71.
worldfoodsituation/wfs-home/en/?no_cache=1 and http://      26	
                                                                Countries in developing regions account for 98 percent
www.fao.org/publications/sofi/en/                           of the world’s undernourished population.
66   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                   FIGURE 17
                   Number of undernourished people in the world, 1969–71 to 2010


                   Millions
                   1 050
                                                                                                                         2009

                   1 000


                     950
                                                                                                                2008
                                                                                                                          2010
                     900
                           1969–71

                                                                         1990–92
                     850                                                                         2000–02
                                                   1979–81
                                                                                                               2005-07
                     800

                                                                                     1995–97
                     750


             Notes: Figures for 2009 and 2010 are estimated by FAO with input from the United States Department of Agriculture,
             Economic Research Service. Full details of the methodology are provided in the technical notes available at
             www.fao.org/publication/SOFI/EN/.
             Source: FAO, 2010g.



                   FIGURE 18
                   Proportion of population that is undernourished in developing regions,
                   1969–71 to 2010


                   Percentage
                   35 1969–71

                   30

                   25
                                                 1979–81
                                                                         1990–92
                   20                                                                                                    2009
                                                                                                  2000–02         2008

                   15                                                                1995–97                  2005–07     2010

                   10

                    5

                    0


             Source: FAO, 2010g.


               Most of the world’s 925 million hungry                    is found in sub-Saharan Africa, where in
             people (62 percent of the total) live in                    2005–07 (the latest period with complete
             Asia and the Pacific, the world’s most                      information by country) 30 percent of the
             populous region, followed by sub-Saharan                    total population were estimated to be
             Africa, home to 26 percent of the world’s                   undernourished, although large variations
             undernourished population (Figure 19). The                  occur among countries. While the prevalence
             highest prevalence of undernourishment                      of hunger is lower in Asia and the Pacific
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                      67
(16 percent), Latin America and the                   Although international food commodity
Caribbean (9 percent) and the Near East and           prices fell in 2009, they remained high
North Africa (7 percent), it varies greatly           relative to prior years, and data through to
by subregion and by country within these              October 2010 indicate an increase in the FPI
regions.                                              from 2009 to 2010. Moreover, high domestic
                                                      prices have persisted in many countries, as
Vulnerability of global food security                 the decline in international prices was slow
to shocks                                             in being transmitted to domestic markets.
The events of the past few years have                    While food prices remained above their
highlighted the vulnerability of global               pre-crisis level, reduced incomes caused by
food security to major shocks – both in               the financial crisis had a detrimental effect
the global agricultural markets and in the            on access to food, leading to a further
world economy. The food price crisis and              sharp increase in global undernourishment
the ensuing economic crisis reduced the               levels. According to estimates of growth
purchasing power of large segments of the             in per capita GDP (approximated using
population in many developing countries,              International Monetary Fund [IMF]
severely curtailing their access to food and          estimates of growth in total GDP minus
thus undermining their food security.                 population growth rates), the global GDP
   The rise in global undernourishment                per capita contracted in 2009, with the
numbers in 2008 was a result of the spike             advanced economies affected more than
in food prices from 2007 to 2008. From a              the economies of the developing world
historical perspective, the price developments        (Figure 21). However, per capita GDP
in this period are not unprecedented, with            declined or stagnated in all developing
markets exhibiting a comparable spike                 regions, with the exception of developing
during the “world food crisis” of 1973–75             Asia – where per capita GDP growth
(Figure 20). Even so, FAO’s Food Price Index          slowed to 5.8 percent, compared with
(FPI) declined in real terms (using the United        more than 10 percent in 2007 (IMF, 2010a;
States GDP deflator) over the period 1961–            IMF, 2010b). The economic recession had a
2010.                                                 severe negative impact on export revenues,
   Since the early 2000s, however, the                foreign direct investments and foreign
downward trend appears to have been                   migrant remittances received by developing
reversed, or at least interrupted, with food          countries (FAO, 2009b). By 2010, the
prices increasing significantly in real terms,        burgeoning recovery of the world economy
culminating in the price spike of 2007–08.            and the significant increases in economic


     FIGURE 19
     Number of undernourished people in 2010, by region (millions)



                            37   19
                      53                        578                       Asia and the Pacific

       239                                                                Sub-Saharan Africa

                                                            Latin America and the Caribbean

                                                                  Near East and North Africa

                                                                          Developed regions



                           Total: 925 million



Source: FAO, 2010g.
68   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                   FIGURE 20
                   FAO Food Price Index in real terms, 1961–2010


                   Index (1990 = 100)
                   400


                   350


                   300


                   250


                   200


                   150


                   100


                     50


                      0
                       1961            1968            1975              1982        1989           1996          2003          2010


             Notes: Calculated using international prices for cereals, oilseeds, meats, dairy products and sugar. The FAO Food Price
             Index is calculated from 1990 to the present on a regular basis; in this figure it has been extended back to 1961 using
             proxy price information. The index measures movements in international prices and not necessarily domestic prices.
             The United States GDP deflator is used to express the Food Price Index in real rather than nominal terms.
             Source: Calculations by FAO.


             growth rates underpinned the reduction in
             global undernourishment numbers discussed                          Food production,
             above.                                                             consumption and trade
               In spite of the declining numbers in 2010,                       during the crises
             reflecting the resumption of economic                              Recent trends in global food
             growth and reduction in food prices, the                           production, consumption and trade
             two crises have drawn our attention to the                         According to data and estimates available
             acute vulnerability of poor countries and                          by mid-2010,27 growth in the global food
             populations to global shocks such as those                         production index (measured in constant
             experienced in the most recent years. In                           prices) slowed to about 0.6 percent in 2009,
             addition, localized shocks and emergencies                         following significant increases of 2.6 and
             have affected food security in specific                            3.8 percent respectively in 2007 and 2008 –
             countries as well as at the subnational                            during the food price crisis (Figure 22, page
             level (see Box 12 for a discussion of food                         72). At the same time, global agriculture
             emergencies in countries requiring external
             assistance). Mechanisms to protect the most                        27	
                                                                                    The indices of food production, consumption and trade
             vulnerable populations from the effects of                         in this section are based on data derived from FAO, Food
                                                                                Outlook, June 2010 (FAO, 2010k), updated to reflect
             such shocks are often woefully inadequate.                         production estimates in September 2010. Indices express
             Consequently, vulnerable households may                            production, consumption and trade in constant prices
             be forced to deal with shocks by selling                           and have been computed using international reference
             productive assets, which are very difficult to                     commodity prices averaged during 2004–06. Production
                                                                                indices are net of feed and seedstock. Consumption indices
             rebuild, thus extending and prolonging the                         are derived from estimates of food use. Commodities
             negative impacts of the crisis far beyond its                      covered include wheat, coarse grains, rice, oilseeds,
             immediate effect.                                                  vegetable oils, meat and dairy products.
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                                         69
     FIGURE 21
     Average annual percentage change in GDP per capita at constant prices, 2005–2010


                                                                                                                                  2005

                    World                                                                                                         2006

                                                                                                                                  2007

    Advanced economies                                                                                                            2008

                                                                                                                                  2009

           Emerging and                                                                                                           2010
   developing economies



              Central and
           Eastern Europe



       Commonwealth of
      Independent States




         Developing Asia




            Near East and
             North Africa




      Sub-Saharan Africa




       Latin America and
           the Caribbean


                            -8       -6      -4       -2       0       2         4       6        8      10       12


Notes: Figures from 2010 are projections based on data from the first three quarters of that year, incorporating the most recent estimates made
in October.
Source: Author’s calculations, using data from IMF, 2010a and IMF, 2010b.


has been affected by other shocks, such                      over 2 percent per year (almost 1 percent
as the drought in the Russian Federation                     in per capita terms), fell marginally in per
during the summer of 2010, which caused                      capita terms during the economic recession
the country’s wheat production and                           in 2009. Growth in trade had been around
exports to fall dramatically. Growth of only                 the 4–6 percent range annually before the
0.8 percent is projected for 2010. Global food               financial crisis; in 2009 it contracted and is
consumption, which had been increasing at                    projected to remain negative in 2010.
70   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                Box 12
                Food emergencies


                Food crises affecting individual countries                      assistance for food.1 Food crises can be
                shock and destabilize the food security                         triggered by a number of factors – natural or
                status of part of or the entire population                      human-induced. If the emergency is natural,
                (the newly food-insecure) and worsen                            it may be described as either sudden or slow-
                it for those who were already food-                             onset,2 and if it is human-induced it may be
                insecure prior to the emergency (the                            the result of socio-economic problems3 or
                chronically food-insecure). FAO’s Global                        war/conflict (see figure).
                Information and Early Warning System                               The total number of recorded
                on food and agriculture (GIEWS)                                 emergencies in recent years is far higher
                monitors and disseminates information                           than in the 1980s. Since the mid-1980s, the
                on countries in crisis requiring external                       general trend has been towards an increase


                      Emergencies (by type) in countries requiring assistance, 1981 to 2009

                      Number of countries
                      80

                      70

                      60

                      50

                      40

                      30

                      20

                      10

                        0
                            1981        1985           1989              1993      1997        2001        2005         2009


                                           Human-induced / War                      Human-induced / Socio-economic

                                           Natural / Slow                           Natural / Sudden


                Note: Data on emergencies do not include events taking place in 2010. At the time of writing, floods
                in Pakistan amounted to the world’s largest humanitarian crisis ever, with up to 20 million people affected
                (about 18 percent of the country’s population) and 6 million people in need of food assistance. The crisis
                was far larger than both the tsunami of 2004 and the Haitian earthquake of early 2010 combined.
                Source: FAO.




             Food consumption per capita by                                     the region was particularly hard hit by the
             region                                                             economic downturn.
             The most rapid growth in per capita                                   Food consumption per capita has remained
             consumption of basic foods in recent years                         stagnant-to-falling in the developed regions
             has been recorded in Eastern Europe,                               of North America, Western Europe and
             followed by Latin America and the                                  Oceania. In sub-Saharan Africa, it rose
             Caribbean, then Asia and the Near East and                         between 2000 and 2007, but is estimated
             North Africa (Figure 23, page 72). In these                        to have fallen somewhat on a per-capita
             regions, per capita consumption generally                          basis since then. In this context, however, it
             continued to rise even during the recession.                       is important to bear in mind that estimates
             An exception was Eastern Europe, which saw                         provided in this analysis do not include all
             a decline of some 2 percent in 2009, when                          food items; roots and tubers, for example,
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                         71

in the number of countries affected by             have begun. Countries in protracted crisis
emergencies. The number of human-induced           face a particularly difficult situation.
emergencies seems to have increased the            According to The State of Food Insecurity
most, with war/conflict accounting for most        in the World 2010 (FAO, 2010g), 22
of them. Over the past decade and a half, the      countries are currently considered to be in
frequency of sudden-onset natural disasters        a state of protracted crisis. Protracted crisis
appears to have been on an upward trend.           situations are characterized by recurrent
   From 1981 to 2009, the region with the          natural disasters and/or conflict, longevity
largest number of countries experiencing           of food crises, breakdown of livelihoods
emergencies was Africa, followed by Asia,          and insufficient institutional capacity to
Latin America and the Caribbean, Eastern           react to the crisis. Such countries need
Europe, Commonwealth of Independent                to be considered as a special category
States (CIS) and Oceania. The high incidence       with special requirements in terms
in Africa is explained in part by the relatively   of interventions by the development
large number of countries in the region            community. (For a detailed discussion
(44 are assessed by GIEWS), but also by            of the special situation of countries in
civil unrest occurring in many countries as        protracted crisis, see FAO, 2010g.)
well as numerous slow-onset disasters. The
number of African countries experiencing
emergencies has ranged from around 15
to 25 annually, with the exception of the
late 1980s, when the number was closer to
10. Of the 23 countries considered in the
Asian region, the number experiencing
emergencies has increased from around 5
annually during the period 1981–2002 to            1
                                                     	Some countries that have consistently funded
around 10 from 2003 to 2009. The number               their own response to emergencies rather
                                                      than seeking assistance from the international
of countries affected in Latin America and            community are excluded from the information
the Caribbean is relatively small but has             collected and disseminated by GIEWS.
fluctuated over the time period, whereas
                                                   2
                                                    	Natural sudden emergencies include sudden onset
                                                      disasters such as floods, cyclones, hurricanes,
in Eastern Europe and the CIS it has been             earthquakes, volcanoes, and locusts. Slowly
decreasing.                                           developing natural disasters such as drought,
                                                      adverse weather, and transboundary pests and
   Just as the effects of economic shocks on          diseases are classified as natural slow emergencies.
hunger do not disappear entirely when prices       3
                                                     	Examples of human-induced socio-economic
                                                      emergencies are crises caused by commodity price
recover and economic growth resumes, the
                                                      collapses/spikes, loss of export markets, currency
impacts of crises on food security may also           problems, land tenure problems and health-
persist long after relief and recovery efforts        related crises.




which are widely consumed in sub-Saharan           production, including structural causes
Africa, have not been included.                    and weather-related factors. Generally,
                                                   production in industrialized countries and
Food production by region                          the “BRIC” countries28 responded most to the
The global production estimates for the            high crop prices of 2007 and 2008. However,
period 2006–10 presented in Figure 22              over the last decade the strongest production
illustrate a global production response            growth was achieved by the LDCs and the
stimulated by high, then falling food prices.      “rest of the world” (Figure 24, page 73).
However, more detailed regional and                  The two geographic regions that
national data underlying the aggregates            experienced the strongest growth in food
present more complex patterns, reflecting
the impact of other influences on agricultural     28	
                                                         Brazil, Russian Federation, India and China.
72                   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




     FIGURE 22
     Annual growth in global food production, consumption and trade, 2006–2010


     Percentage change
     7                                                                                                                       Production


     6                                                                                                                    Consumption


     5                                                                                                                             Trade


     4

     3

     2

     1

     0

    -1
               2006                  2007                  2008                  2009            2010

Note: Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates.
Source: FAO.



     FIGURE 23
     Indices of per capita food consumption by geographic region, 2000–10


     Index (2004–06 = 100)
     115                                                                                                              Northern America
                                                                                                                     Latin America and
     110                                                                                                                 the Caribbean
                                                                                                                        Western Europe
     105                                                                                                                 Eastern Europe
                                                                                                                          Near East and
     100                                                                                                                   North Africa
                                                                                                                    Sub-Saharan Africa
      95                                                                                                                               Asia
                                                                                                                     Oceania and Japan
      90


      85


      80
            2000      2001     2002      2003      2004      2005      2006     2007     2008   2009    2010


Note: Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates.
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                                              73
     FIGURE 24
     Indices of food production by economic group


     Index (2004–06 = 100)
     120                                                                                                                             World
                                                                                                                             BRIC countries
     115
                                                                                                                         OECD countries
     110                                                                                                                              LDCs
                                                                                                                       Rest of the world
     105

     100

       95

       90

       85

       80
              2000              2002              2004               2006               2008               2010


Note: Net of feed and seedstock. Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are
provisional estimates.
BRIC = Brazil, Russian Federation, India and China; LDCs = least-developed countries.
Source: FAO.


production over the last decade – Eastern                     Union (EU), but declined by around 2 percent
Europe and Latin America and the Caribbean                    in 2009 as a result of lower prices and
– had mixed experiences during the food                       unfavourable weather conditions.
price and financial crises (Figure 25). The
Eastern European countries, after recording                   Food exports by region
bumper crops in 2008, were unable to sustain                  Food exports by nearly all regions, fell or
potential growth in the subsequent years, and                 stagnated in 2009 during the economic
the 2010 drought led to substantially reduced                 crisis (Figure 26). From 2000 to 2008, Eastern
levels of crop production in the region.                      Europe saw cumulative export growth of
Latin America and the Caribbean suffered                      around 350 percent; in 2008 it recorded a
weather-related production shortfalls in                      particularly high level of grain production.
2008 but recovered in 2009 and 2010. In Asia,                 However, exports declined the following
growth in food production remained strong                     year and even more significantly as a result
throughout the last decade, generally in the                  of drought in 2010.29 Food exports from
range of 2–4 percent per year, but recorded a                 Western Europe declined, possibly as a result
slowdown in 2009 and 2010.                                    of the rise in the value of the euro as well
   Production failed to grow in 2009 in sub-                  as of successive policy reforms, including
Saharan Africa, which had seen growth in                      the reform of the EU Common Agricultural
the range of 3–4 percent per year over the                    Policy. Strong export performances
previous decade; it is expected to expand                     by countries in Latin America and the
moderately in 2010. The region registering                    Caribbean, for which food exports nearly
the slowest growth in food production                         doubled over the decade, have made this
in recent years is Western Europe, where                      region an increasingly important supplier
production in 2010 is projected to be                         of food to global markets. However, the
only some 5 percent higher than in 2000.
Production did increase in 2007 and 2008                      29	
                                                                  The trade index values by region include trade within
under the effect of high prices and reduced                   the region; this may affect conclusions about relative trade
set-aside requirements in the European                        performance.
74                  TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




     FIGURE 25
     Indices of food production by region, 2000–10


     Index (2004–06 = 100)
     130                                                                                                             Northern America
                                                                                                                    Latin America and
                                                                                                                        the Caribbean
     120
                                                                                                                       Western Europe
                                                                                                                        Eastern Europe
     110
                                                                                                                         Near East and
                                                                                                                          North Africa
     100                                                                                                           Sub-Saharan Africa
                                                                                                                                    Asia
                                                                                                                    Oceania and Japan
      90


      80


      70
             2000     2001     2002      2003      2004      2005      2006      2007   2008   2009     2010


Note: Net of feed and seedstock. Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are
provisional estimates.
Source: FAO.

                             region’s food exports stagnated in volume                     subsequent economic downturn translated
                             terms during the food price crisis and during                 into a decline in import volumes in 2008 and
                             the economic recession. Export volumes                        stagnating levels in 2009 and 2010. During
                             from North America grew by 24 percent                         the last decade, net food imports by sub-
                             over the decade, but growth may have been                     Saharan Africa, measured in constant prices,
                             dampened by the rising use of domestic                        increased more than 60 percent, implying
                             grains for biofuel production.                                a further widening of the food trade
                                                                                           deficit faced by this region over the past
                             Food imports by region                                        several decades, as population growth has
                             Food imports have been rising more rapidly                    outstripped growth in food production.
                             in Asia than in any other region (Figure 27),
                             increasing in volume terms by almost
                             75 percent between 2000 and 2010. Imports
                             continued to grow through the food price
                             crisis and also during the recession, as the
                             region succeeded in sustaining relatively high
                             rates of income growth. Food imports by
                             countries in the Near East and North Africa
                             have also grown, financed by growing oil
                             revenues, but were considerably reduced
                             during the recession. Imports by all other
                             regions also grew significantly over time,
                             with the exception of North America and
                             Oceania, where they remained relatively
                             stagnant. Sub-Saharan Africa’s food import
                             volumes increased during the first half of
                             the decade, but the higher international
                             prices during the food price crisis and the
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                                              75
     FIGURE 26
     Indices of food export volumes by geographic region, 2000–10


     Index (2004–06 = 100)
     200                                                                                                              Northern America
                                                                                                                     Latin America and
     180                                                                                                                 the Caribbean

     160                                                                                                                Western Europe
                                                                                                                         Eastern Europe
     140
                                                                                                                          Near East and
                                                                                                                           North Africa
     120
                                                                                                                    Sub-Saharan Africa
     100                                                                                                                               Asia
                                                                                                                     Oceania and Japan
       80

       60

       40

       20
             2000      2001     2002     2003     2004     2005     2006     2007      2008     2009     2010


Note: Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates.
Source: FAO.




     FIGURE 27
     Indices of food import volumes by geographic region, 2000–10


     Index (2004–06 = 100)
     140                                                                                                              Northern America
     130                                                                                                             Latin America and
                                                                                                                         the Caribbean
     120                                                                                                                Western Europe
     110                                                                                                                 Eastern Europe
                                                                                                                          Near East and
     100                                                                                                                   North Africa
       90                                                                                                           Sub-Saharan Africa
                                                                                                                                       Asia
       80
                                                                                                                     Oceania and Japan
       70

       60

       50

       40
             2000     2001      2002     2003     2004     2005     2006     2007      2008     2009     2010


Note: Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates.
Source: FAO.
76                TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                                                                                         food price crisis and have shown substantial
                          Recent trends in agricultural                                  and highly correlated volatility since 2006
                          prices: a higher price plateau,                                (Figure 29). More recently, from June
                          and greater price volatility                                   through October 2010, prices of cereals, oils
                                                                                         and sugar have increased, largely explaining
                          International prices for agricultural                          the increase in the FPI over the same period.
                          commodities                                                    The volatility of sugar prices, particularly
                          As discussed above, price developments in                      since 2005, has been even more pronounced
                          food commodity markets, especially those                       than that of the other commodities
                          used to calculate the FPI (cereals, oils, dairy,               contained in the FPI. Meat prices have
                          meats and sugar), can have a critical impact                   fluctuated little in comparison with those of
                          on global food security. Close monitoring of                   cereals, oils, dairy products and sugar.
                          market developments is therefore crucial.                         Among other agricultural commodities
                          This section reviews recent developments in                    that are not part of the FPI (Figure 28),
                          international and domestic food markets,                       international fruit prices moved closely
                          discusses the current situation and identifies                 together with those of the FPI, exhibiting
                          major issues of concern for future food                        a spike during the food price crisis and a
                          security.                                                      decline during the subsequent financial crisis.
                            During the food price crisis of 2007–08                      The price of beverage products moved less
                          the FPI increased sharply (Figure 28). At the                  closely with prices of commodities contained
                          time of writing, the most recent data shows                    in the FPI. Raw material prices were generally
                          the FPI to have increased again from June                      not affected by the rise in other commodity
                          through October 2010. In fact, by October                      prices during the food price crisis but
                          2010, the FPI was just 8 percent below its                     decreased significantly in response to the
                          peak in June 2008.                                             economic downturn in 2009 before moving
                            Among the commodities included in the                        upwards again in response to economic
                          FPI, prices for cereals, oils and dairy products               recovery, reflecting the high income elasticity
                          showed a sharp increase during the 2007–08                     of demand for this group of commodities.


     FIGURE 28
     FAO Food Price Index and indices of other commodities (fruits, beverages and raw materials),
     October 2000–October 2010


     Index (2002–04 = 100)
     250                                                                                                             FAO Food
                                                                                                                    Price Index
                                                                                                                         Fruits
     200                                                                                                            Beverages
                                                                                                                 Raw materials


     150



     100



      50



       0
            Oct    Oct       Oct        Oct        Oct        Oct       Oct        Oct    Oct    Oct     Oct
           2000   2001      2002       2003       2004       2005      2006       2007   2008   2009    2010


Source: FAO.
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                              77
     FIGURE 29
     Indices of prices of commodities included in the FAO Food Price Index (cereals, oils, dairy,
     meat and sugar), October 2000–October 2010


     Index (2002–04 = 100)
     400                                                                                                            Cereals
                                                                                                                       Oils
     350
                                                                                                                     Dairy

     300                                                                                                             Sugar
                                                                                                                     Meat
     250

     200

     150

     100

      50

        0
             Oct    Oct    Oct    Oct    Oct    Oct    Oct        Oct       Oct       Oct      Oct
            2000   2001   2002   2003   2004   2005   2006       2007      2008      2009     2010


Sources: FAO and IMF.


  Although prices of basic commodities have     double threat to the food security of poor
declined from the peak levels they attained     consumers, as domestic food prices remained
during the food price crisis, by the third      high while income growth slowed or turned
quarter of 2010 prices of all commodities in    negative.
the FPI remained significantly higher than        In 2010, this double threat seems to
those preceding the crisis. According to        have diminished relative to the preceding
projections in the OECD-FAO Agricultural        period, particularly as many emerging and
Outlook 2010–2019 (OECD-FAO, 2010), real        developing countries appeared to have
commodity prices over the next decade are       recovered from the economic slowdown
expected to be, on average, higher than         earlier and more strongly than expected
they were in the period 2000–10. Factors        (See IMF, 2010c ). Moreover, the most recent
underlying the projected higher agricultural    available data on domestic prices indicate
commodity prices include higher production      that cereal prices in developing countries
costs, increased demand by emerging and         have declined significantly from their peaks
developing countries and growing production     in 2008, although at the time of writing the
of biofuels from agricultural feedstocks.       price of wheat on international markets had
                                                again risen sharply. Data on cereal wholesale
Domestic food prices in developing              prices in 74 developing countries collected
countries                                       by GIEWS (FAO, 2010j) show that, by early
Last year’s edition of this report discussed    2010, such prices had fallen in nominal terms
price transmission from international to        relative to their peak values in 90 percent of
domestic markets (FAO, 2009a). After the        the countries. After adjusting for inflation,
food price crisis, domestic commodity           more than 98 percent of price quotes had
prices in many countries were slow in           fallen from their peaks by the start of 2010.
moving downwards, despite the rapid fall        Nevertheless, although domestic prices in
in international prices, suggesting a slow      developing countries have declined, they
or low degree of transmission to domestic       remain high compared with before the
consumers. This phenomenon created a            food price crisis. Indeed, in early 2010, more
78                   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




                             than 80 percent of the inflation-adjusted                          increased fluctuations in agricultural and
                             wholesale cereal price quotes remained                             food production. A further source of price
                             above their average level in 2006 – the year                       volatility is the expanding production of
                             prior to the food price crisis.                                    biofuels based on agricultural feedstocks,
                                                                                                which could tighten the link between prices
                             Growing concerns over price                                        of agricultural commodities, especially
                             volatility                                                         maize, and developments and conditions
                             The extreme variability of prices of basic                         in international energy markets, implying
                             food commodities over the most recent                              an increased transmission of fluctuations in
                             period has caused considerable concern.                            energy prices onto markets for agricultural
                             Episodes of high prices are detrimental                            and food commodities. The close
                             to food security, and the high uncertainty                         relationship between the production costs of
                             associated with price volatility affects                           ethanol from maize and of petrol from crude
                             producer viability and may lead to reduced                         oil is illustrated in Figure 31. This also implies
                             agricultural investments. Data on price                            that prices for crude oil and for maize now
                             volatility over a longer period (starting in                       appear to be closely related. In the light of
                             1957), show that high price volatility such                        current uncertainties surrounding future oil
                             as that recently experienced is not far out                        prices and their impact both on demand for
                             of line with past experiences (Figure 30).                         biofuels and on agricultural input markets
                             Indeed, periods of high price volatility are                       (e.g. markets for fertilizers, mechanization,
                             not new to agriculture, but there are fears                        and transportation), concerns over increased
                             that price volatility may be increasing.                           agricultural price volatility from these new
                               Increased disquiet over greater volatility                       sources appear to have some justification.
                             of food prices is related to the emergence                         Furthermore, higher real crop prices have
                             of new factors contributing to it. One                             also recently induced higher production
                             important factor is the expected increase                          in some areas where yield volatility is also
                             in severe weather events as a consequence                          higher, such as the grain-producing areas
                             of climate change, which could lead to                             around the Black Sea. To the extent that


     FIGURE 30
     Historic annualized volatility of international grain prices


     Percentage
      70                                                                                                                          Wheat
                                                                                                                                  Maize
      60                                                                                                                             Rice


      50


      40


      30


      20


      10


       0
           1957   1961   1965   1969     1973    1977    1981    1985     1989    1993   1997   2001   2005   2009


Note: Some price variability can be predicted (e.g. seasonal variation, business cycles or other trending behaviour). The figure shows the coefficient
of variation of prices after the predictable component has been removed from the observed values (for explanation, see OECD-FAO, 2010, p. 57,
footnote 5). Values close to zero indicate low volatility, higher values denote greater volatility.
Source: OECD-FAO, 2010.
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                        79
BOX 13
Implied volatility as a measure of uncertainty


How organized commodity exchanges                     Implied volatilities for wheat, maize
perceive and value uncertainty is                   and soybeans since 1990 are presented
important for future decisions on                   in Figure A and movement over the
production, trade and investment.                   period October 2007–October 2010 is
Implied volatility represents the market’s          presented in Figure B. Market perceptions
expectation of how much the price of a              of volatility as estimated by the
commodity is likely to fluctuate in the             implied price volatility have increased
future. It is derived from the prices of            systematically, with a sharp peak in 2008.
derivative contracts, namely options,               In the aftermath of the 2007–08 market
which are priced on the basis of the                turmoil, implied volatilities fell as markets
market’s estimates of future prices as              began to stabilize. However, around mid-
well as the uncertainty surrounding these           2010 implied volatility started moving
estimates. The more divergent are traders’          upwards again when doubts began to
expectations about future prices, the               emerge over Russia’s ability to meet
higher the underlying uncertainty and               grain export commitments, followed
thus the implied volatility. (For a more            by similar concerns over United States
detailed discussion of the concept and the          maize prospects and expected demand
methodology, see FAO, 2010k.)                       outstripping soybean supply.


    Implied price volatility of wheat and maize
    A                                                                            1990–2010
    Percentage
     45
     40
     35
     30
     25
     20
     15
     10
      5
      0
           1990   1992      1994   1996    1998    2000   2002       2004     2006     2008     2010



    B                                                                    October 2007–October 2010

    Percentage
    60

    50

    40

    30

    20

    10

     0
           Oct       Apr             Oct          Apr             Oct           Apr             Oct
          2007       2008           2008          2009           2009           2010           2010

                               Wheat              Maize             Soybeans

Source: FAO.
80                   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




     FIGURE 31
     Co-movement of energy production costs: ethanol from maize versus petrol from crude oil,
     October 2006–October 2010


     US cents/litre
      80                                                                                                                      Petrol from
                                                                                                                                crude oil
      70                                                                                                                    Ethanol from
                                                                                                                                  maize
      60

      50

      40

      30

      20

      10

       0
            Oct      Apr           Oct         Apr            Oct         Apr             Oct     Apr        Oct
           2006      2007         2007         2008          2008         2009           2009     2010      2010


Notes and sources: FAO calculation using ethanol production, simple cost budgets and IMF commodity price statistics.
The petroleum equivalent is the per-litre price of crude oil adjusted to an ethanol energy basis, plus a cost adjustment for processing to gasoline.
Ethanol from maize is the cost of producing ethanol, net of by-product revenues, on a per-litre basis. Source prices are Brent Crude oil
and US Gulf #2 Maize.


                             these areas increase their export market                           Europe, but has continued to grow in other
                             shares, greater supply volatility from these                       regions, although more slowly in Eastern
                             regions may affect price volatility.                               Europe. Despite some fluctuations during
                               A highly relevant factor in recent times                         the crises, food production increased over
                             has been the uncoordinated national policy                         the last decade in all regions except Western
                             responses to fluctuations in international                         Europe, as well as Japan and Oceania. With
                             prices, which may exacerbate market                                the exception of Eastern Europe and Latin
                             volatility. The impact of such policies was                        America and the Caribbean, which represent
                             discussed in last year’s edition of this report                    key future food suppliers, supplies from
                             (FAO, 2009a). A further issue is the role                          traditional exporters appear to be increasing
                             of speculation in recent market volatility;                        more slowly than in the past. Food imports
                             this has been surrounded by considerable                           decreased as a result of the price and
                             controversy, and further research evidence                         financial crises in all regions except Asia and
                             on the topic is needed.                                            the Near East and North Africa.
                                                                                                   Commodity prices appear to be on a
                             Summary of the current situation                                   higher plateau and are projected to remain
                             and future prospects for agricultural                              at levels above those of the pre-crisis period
                             markets                                                            while markets have remained highly volatile.
                             In the aftermath of the food price and                             Market volatility and its possible implications
                             financial crises, global food and agricultural                     for food security have become increasingly
                             commodity markets appear to be                                     problematic for policy-makers worldwide.
                             characterized both by higher price levels                          In an environment of increased uncertainty,
                             and increased uncertainty. During the crises,                      policy responses to the situation will be
                             per capita food consumption decreased                              a critical determinant of future market
                             marginally in sub-Saharan Africa as well                           developments and their possible implications
                             as in North America, Oceania and Western                           for food security.
W o r ld food a n d a g r icul t u r e i n r e v iew

                                                                                                                    81
   BOX 14
   Price volatility and FAO’s Intergovernmental Groups on Grains and Rice


  The extraordinary joint intersessional            •	 insufficient market transparency at all
  meeting of FAO’s Intergovernmental                   levels, including in relation to futures
  Group on Grains and Intergovernmental                markets;
  Group on Rice held in Rome on                     •	 growing linkages with outside
  24 September 2010 recognized that                    markets, in particular the impact of
  unexpected price hikes and volatility                “financialization” on futures markets;
  are amongst the major threats to food             •	 unexpected changes triggered by
  security. They pointed to a number of root           national food-security situations;
  causes that need to be addressed:                 •	 panic buying and hoarding.
    •	 the lack of reliable and up-to-date
       information on crop supply and
       demand and export availability;            Source: FAO, 2010l.



                                                  of appropriate safety nets and social
Conclusions                                       programmes to protect the food-insecure
The world food-price crisis, followed by the      from the immediate impact of shocks like
global financial crisis and economic recession,   these, as well as the critical and urgent
pushed the number of undernourished               need to boost the productive capacity of
people in the world to unprecedented              developing countries and to enhance their
levels in 2008 and 2009. Estimates indicate       resilience to shocks.
that the number of undernourished people             The food price crisis has highlighted a series
declined in 2010, as food prices fell from        of concerns specific to the agriculture sector
their peak levels and global economic             and agricultural markets. First, the most
conditions began to improve. However, levels      recent projections by FAO and OECD indicate
of undernourishment remain very high by           that, although international prices fell fairly
historical standards, and concerns both for       rapidly from the peak levels attained during
the world economy and for world agriculture       the global food-price crisis, they remain
continue to be at the top of the international    higher than they were before the crisis and
policy agenda. In October 2010, the IMF           it appears that higher food prices are here
indicated that “macroeconomic recovery is         to stay. Agriculture faces higher production
proceeding broadly as expected, although          costs, increasing demand from rapidly growing
downside risks remain elevated” (IMF, 2010b,      countries in developing regions and expanding
p. 1). At the same time, the sudden rise in       biofuel production. As a result, prices are
cereal prices from June through October           projected to increase over the next decade
2010 raised fears of a new food-price crisis.     and to continue to be at levels, on average,
   Whatever the short-term outlook for            above those of the past decade. There is by
the world economy, agriculture and food           now a widely recognized need to significantly
security, a number of lessons with long-term      increase investments in agriculture in
implications appear to have emerged or to         order to generate environmentally
have been confirmed from the developments         sustainable productivity increases and
of the past few years.                            expand production, while at the same time
   The experiences of the food price and          enhancing the contribution of agriculture to
financial crises have provided a sharp            economic growth and poverty alleviation.
reminder of the vulnerability of world               A second source of concern is the recent
food security to shocks in the global food        turbulence in international agricultural
system and the world economy and have             markets and the risk of increased price
demonstrated how rapidly an already               volatility. Price volatility has always been a
unacceptable level of food insecurity in the      feature of agricultural markets; however, a
world can deteriorate in the face of such         number of trends appear to be accentuating
events. This has underscored the importance       this phenomenon. Climate change may
82   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




             be leading to more frequent and extreme                     security and hunger-reduction efforts, there
             weather events and to the consequent risk                   is a need to address issues of governance on
             of shocks to agricultural markets. Expanding                global agricultural markets with a view to
             production of biofuels based on agricultural                confronting the problem of price volatility
             commodities will make agricultural markets                  and avoiding counter-productive “beggar-
             much more dependent on developments in                      thy-neighbour” policy responses. Necessary
             global energy markets.                                      steps would include improved regulation
               A specific “human-induced” threat to                      of markets, greater market transparency,
             market stability is that of uncoordinated                   improved and timely statistics on food
             national policy responses to increasing food                commodity markets, establishment of an
             prices. Because such measures are based                     appropriate level of emergency stocks and
             exclusively on concerns about domestic food                 provision of adequate and appropriate
             security, with little regard for their effects              safety nets. The recent food and financial
             on trading partners, they may exacerbate                    crises, the uncoordinated policy responses
             international market volatility and                         and continuing fears over global food-
             jeopardize global food security.                            market turmoil have underscored the
               Given the importance of international                     urgent need for action by the international
             food commodity markets for global food                      community.
Part III
Statistical annex
Part III
S t a t is t ic a l a n n ex

                                                                                         85
Notes on the annex tables



Symbols

The following symbols are used in the tables:

..			              = data not available
0 or 0.0		         = nil or negligible
blank cell	        = not applicable
(A)		              = FAO estimate

Numbers displayed in the tables might be slightly different from the
ones obtained from the original data sources because of rounding or
data processing. To separate decimals from whole numbers a full point
(.) is used.



Technical notes

Table A1: Total population, female share of population and
rural share of population in 1980, 1995 and 2010
Source: FAO, 2010b.

Total population
The de facto population in a country, area or region as of 1 July of the
year indicated. Figures are presented in the thousands.

Female share of population
The total number of women divided by the total population and
multiplied by 100.

Rural share of population
The de facto population living in areas classified as rural (according to
the criteria used by each country) divided by the total population and
multiplied by 100.

Table A2: Female share of national, rural and urban population
aged 15–49, most recent and earliest observations
Source: United Nations, 2008.
Data presented are not directly comparable among countries because
they vary in terms of year(s) of data collection. For details, refer to
United Nations (2008).

Rural/urban
The population classified as rural or urban according to criteria used
by each country.
86   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




          Table A3: Economically active population, female share of
          economically active population and agricultural share of
          economically active women in 1980, 1995 and 2010
          Source: FAO, 2010b.

          Economically active population
          The number of all employed and unemployed persons (including
          those seeking work for the first time). The term covers employers;
          self-employed workers; salaried employees; wage earners; unpaid
          workers assisting in a family, farm or business operation; members
          of producers’ cooperatives; and members of the armed forces. The
          economically active population is also referred to as the labour force.

          Female share of economically active population
          The share of all employed and unemployed persons who are female
          (including those seeking work for the first time). The term covers
          female employers; self-employed workers; salaried employees;
          wage earners; unpaid workers assisting in a family, farm or business
          operation; members of producers’ cooperatives; and members of
          the armed forces. The economically active female population is also
          referred to as the female labour force.

          Agricultural share of economically active women
          The share of the economically active female population who are
          engaged in or seeking work in agriculture, hunting, fishing or forestry.

          Table A4 : Economically active population, agricultural share of
          economically active population and female share of economically
          active in agriculture in 1980, 1995 and 2010
          Source: FAO, 2010b.

          Economically active population
          See notes for Table A3.

          Agricultural share of the economically active population
          The share of the economically active population who are engaged in
          or seeking work in agriculture, hunting, fishing or forestry.

          Female share of economically active in agriculture
          The share of the economically active population in agriculture who are
          women.

          Table A5: Share of households in rural areas that are female-
          headed, most recent and earliest observations, and total
          agricultural holders and female share of agricultural holders,
          most recent observations
          Sources: Measure DHS/ICF Macro, 2010 (columns 1 and 2), and FAO,
          2011 (forthcoming) (columns 3 and 4).

          Households
          Values are based on de jure members, i.e. usual residents.

          Agricultural holder
          The definition of agricultural holder varies from country to country,
          but widely refers to the person or group of persons who make the
S t a t is t ic a l a n n ex

                                                                                         87
major decisions regarding resource use and exercise management
control over the agricultural holding operation. The agricultural
holder has technical and economic responsibility for the holding and
may undertake all responsibilities directly, or delegate responsibilities
related to the management of day-to-day work. The agricultural
holder is often, but not always, the household head.

Symbols used
(B)
    Indicates that the source is FAO (2010f).
(1)
    Data are from the Northeast Region only.
(2)
    In Kyrgyzstan and Lebanon the landless holders are without arable
land (rather than without any land).
(3)
    In the case of Viet Nam, farm owners (rather than agricultural
holders) were counted.
(4)
    Data were collected for ever-married women aged 10-49. Women
age 10–14 were removed from the data set and the weights
recalculated for the 15–49 age group.
(5)
    Data were collected for women aged 10-49 and indicators were
calculated for women 15-49.
(6)
    Data were collected for women aged 13-49 and indicators were
calculated for women 15-49.
(7)
    For Austria, Belgium, Denmark, Finland, Germany, Greece, Ireland,
Luxembourg, Netherlands, Norway, Portugal and Sweden, holders
include “holders without agricultural land”.

Table A6: Share of adult population with chronic energy
deficiency (CED – body mass index less than 18.5) by sex and
share of children underweight by sex, residence and household
wealth quintile, most recent observations
Source: WHO, 2010.

Share of women with CED
The share of adult women who have a body mass index (BMI) (kg/m2)
less than 18.5.

Share of men with CED
The share of adult men who have a body mass index (BMI) (kg/m2) less
than 18.5.

Share of children underweight
Underweight prevalence, among children under five years of age
(0–59 months unless otherwise noted) is estimated as the share of
those children whose weight is below minus two standard deviations
from the median weight for age of the National Center for Health
Statistics (NCHS)/WHO/Centers for Disease Control and Statistics (CDC)
international standard reference population.

Residence
Criteria used to define rural and urban are often country-specific; data
in this table are based on national definitions.

Household wealth quintile
Household ownership of assets and access to services is measured and
principle components analysis is used to calculate an index, the value
of which is assigned to each member of the household. The index
88   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




          scores for the entire population are then arranged in ascending order
          and the distribution is divided at the points that form the five 20
          percent cohorts.

          Symbols used and additional notes on the data
          (C)
              Indicates no observations available for both men and women from
          the same year for chronic energy deficiency (CED).
          For share of underweight children, observations are for children aged
          0–59 months unless indicated by:
          (1)
              6–59 months, (2) 0–71 months, (3) 3–59 months (4) 6–39 months and (5)
          24–59 months.

          The national BMI data displayed in this table are empirical and it
          has been verified that they apply internationally recommended
          BMI cut-off points. However, it should be noted the data presented
          are not directly comparable because they vary in terms of sampling
          procedures, age ranges and the year(s) of data collection. For details,
          refer to WHO, 2010.



          Country groups and aggregates

          The tables in this publication contain country group composites for all
          indicators for which aggregates can be calculated. These are generally
          weighted averages that are calculated for the country groupings as
          described below. In general, an aggregate is shown for a country
          grouping only when data are available for at least half the countries
          and represent at least two-thirds of the available population in that
          classification.



          Country and regional notes

          Regional and subregional groupings, as well as the designation of
          developing and developed regions, follow the standard country or
          area codes for statistical use developed by the United Nations Statistics
          Division. They are available at http://unstats.un.org/unsd/methods/
          m49/m49regin.htm
            Whenever possible, data from 1992 or later are shown for the
          individual countries of Armenia, Azerbaijan, Belarus, Estonia,
          Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russian
          Federation, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. Data
          before 1992 are shown under the Union of Soviet Socialist Republics
          (“USSR” in the table listings).
            Separate observations are shown for Belgium and Luxembourg
          whenever possible.
            Unless otherwise noted, data for China include data for Hong Kong
          Special Administrative Region of China, Macao Special Administrative
          Region of China, and Taiwan Province of China. Data for China,
          mainland do not include those areas.
            Data are shown when possible for the individual countries formed
          from the former Czechoslovakia – the Czech Republic and Slovakia.
          Data before 1993 are shown under Czechoslovakia.
S t a t is t ic a l a n n ex

                                                                                      89
  Data are shown for Eritrea and Ethiopia separately, if possible; in
most cases before 1992 data on Eritrea and Ethiopia are aggregated
and presented as Ethiopia PDR.
  Data for Yemen refer to that country from 1990 onward; data
for previous years refer to aggregated data of the former People’s
Democratic Republic of Yemen and the former Yemen Arab Republic.
  Data for years prior to 1992 are provided for the former Yugoslavia
(“Yugoslavia SFR” in the table listings). Observations from the years
1992 to 2006 are provided for the individual countries formed from
the former Yugoslavia; these are Bosnia and Herzegovina, Croatia,
the former Yugoslav Republic of Macedonia, and Slovenia, as well
as Serbia and Montenegro. Observations are provided separately
for Serbia and for Montenegro after the year 2006 when Serbia and
Montenegro separated and became two independent states.
90                  TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A1
Total population, female share of population and rural share of population in 1980, 1995 and 2010

                                                                                         Population
                                                   Total                                Female share                  Rural share
                                                 (Thousands)                             (% of total)                 (% of total)

                                     1980           1995          2010           1980       1995        2010   1980      1995        2010


WORLD                              4 428 081     5 713 069      6 908 685        49.7       49.6        49.6   60.9      55.3        49.4


COUNTRIES IN DEVELOPING
                                   3 299 983     4 538 389      5 671 456        49.0       49.1        49.2   70.7      62.4        54.7
REGIONS


AFRICA                               482 232       726 284      1 033 043        50.3       50.2        50.1   72.1      65.8        59.9


Sub-Saharan Africa                   389 751       593 182       863 315         50.4       50.4        50.2   76.1      69.3        62.5


Eastern Africa                       143 491       219 874       327 187         50.6       50.6        50.4   85.3      80.4        76.2
Burundi                                 4 130         6 167        8 519         51.9       51.3        50.9   95.7      92.8        89.0
Comoros                                   384          615           890         49.7       49.8        49.9   76.8      71.7        71.8
Djibouti                                  340          624           879         50.3       50.2        50.1   27.9      20.2        11.9
Eritrea                                               3 206        5 224                    51.2        50.8             83.4        78.4
Ethiopia                                            56 983        84 976                    50.3        50.2             86.1        82.4
Ethiopia PDR (A)                      37 878                                     50.4                          89.3
Kenya                                 16 261        27 492        40 863         50.2       50.2        50.0   84.3      81.0        77.8
Madagascar                              8 604       13 121        20 146         49.7       50.0        50.2   81.5      74.2        69.8
Malawi                                  6 215       10 144        15 692         51.6       50.6        50.3   90.9      86.7        80.2
Mauritius                                 966         1 129        1 297         50.7       50.1        50.5   57.7      56.7        57.4
Mozambique                            12 138        15 945        23 406         51.1       52.3        51.3   86.9      73.8        61.6
Réunion                                   506          664           837         51.2       51.1        51.3   46.6      13.9         6.0
Rwanda                                  5 197         5 440       10 277         52.0       52.1        51.5   95.3      91.7        81.2
Seychelles                                  66             76         85         50.0       50.0        49.4   50.0      50.0        44.7
Somalia                                 6 434         6 521        9 359         50.6       50.5        50.4   73.2      68.6        62.5
Uganda                                12 655        20 954        33 796         50.2       50.2        49.9   92.5      88.3        86.7
United Republic of Tanzania           18 661        29 972        45 040         50.6       50.5        50.1   85.4      79.5        73.6
Zambia                                  5 774         9 108       13 257         50.3       50.3        50.1   60.2      62.9        64.3
Zimbabwe                                7 282       11 713        12 644         50.3       50.6        51.6   77.6      68.3        61.7


Middle Africa                         53 793        86 423       128 908         50.9       50.6        50.4   71.0      65.2        56.9
Angola                                  7 854       12 539        18 993         50.8       50.7        50.7   75.7      56.0        41.5
Cameroon                                9 080       14 054        19 958         50.4       50.3        50.0   68.1      54.7        41.6
Central African Republic                2 269         3 335        4 506         50.9       50.9        50.9   66.1      62.8        61.1
Chad                                    4 608         7 128       11 506         50.8       50.5        50.3   81.2      78.1        72.4
Congo                                   1 815         2 782        3 759         50.3       50.2        50.1   52.1      43.6        37.9
Democratic Republic
                                      27 170        44 921        67 827         51.1       50.6        50.4   71.3      71.6        64.8
of the Congo
Equatorial Guinea                         220          452           693         51.4       50.7        50.4   72.3      61.1        60.3
Gabon                                     682         1 084        1 501         50.7       50.5        50.0   45.3      24.6        14.0
Sao Tome and Principe                       95         128           165         50.5       50.0        50.3   66.3      51.6        37.6


Northern Africa                      112 990       163 943       212 920         49.8       49.7        49.8   59.9      53.6        48.3
Algeria                               18 811        28 265        35 423         49.8       49.6        49.5   56.5      44.0        33.5
S t a t is t ic a l a n n ex

                                                                                                                                 91
TABLE A1 (cont.)

                                                                         Population
                                        Total                           Female share                            Rural share
                                      (Thousands)                        (% of total)                             (% of total)

                           1980          1995         2010       1980       1995        2010           1980          1995        2010


Egypt                      44 433        63 858       84 474     49.9       49.6        49.7           56.1              57.2    57.2
Libyan Arab Jamahiriya      3 063          4 834       6 546     46.6       47.6        48.4           29.9              24.0    22.1
Morocco                    19 567        26 951       32 381     50.0       50.3        50.9           58.8              48.3    43.3
Sudan                      20 509        30 841       43 192     49.9       49.7        49.6           80.0              68.7    54.8
Tunisia                     6 457          8 935      10 374     49.3       49.5        49.7           49.4              38.5    32.7
Western Sahara                150           259          530     46.0       47.9        47.2           22.7              12.7    18.1


Southern Africa            32 972        47 240       57 968     50.5       50.9        50.7           55.3              48.6    41.2
Botswana                      985          1 550       1 978     51.2       50.6        49.9           83.6              51.0    38.9
Lesotho                     1 296          1 726       2 084     53.9       53.4        52.7           88.5              83.0    73.1
Namibia                     1 013          1 620       2 212     51.2       51.1        50.7           74.9              70.2    62.0
South Africa               29 075        41 375       50 492     50.3       50.7        50.7           51.6              45.5    38.3
Swaziland                     603           969        1 202     52.6       52.0        51.0           82.3              77.0    74.5
 
Western Africa            138 986       208 804      306 060     50.1       50.0        49.9           72.8              64.1    55.4
Benin                       3 560          5 723       9 212     51.6       50.3        49.5           72.7              63.3    58.0
Burkina Faso                6 862        10 127       16 287     50.5       50.6        50.0           91.2              84.9    79.6
Cape Verde                    289           398          513     54.3       52.8        52.0           76.5              51.3    38.8
Côte d’Ivoire               8 419        14 981       21 571     48.0       48.2        49.1           63.1              58.6    49.9
Gambia                        616          1 085       1 751     50.6       50.5        50.4           71.6              56.1    41.9
Ghana                      11 026        17 245       24 333     49.5       49.4        49.3           68.8              59.9    48.5
Guinea                      4 628          7 478      10 324     49.8       49.5        49.5           76.4              70.5    64.6
Guinea-Bissau                 836          1 166       1 647     50.6       50.5        50.5           82.4              70.2    70.0
Liberia                     1 910          1 945       4 102     50.7       50.6        50.3           64.8              50.0    38.5
Mali                        7 183          9 549      13 323     49.9       50.5        50.6           81.5              74.5    66.7
Mauritania                  1 525          2 270       3 366     49.8       49.7        49.3           72.7              60.2    58.6
Niger                       5 922          9 302      15 891     50.2       50.4        49.9           86.6              84.2    83.3
Nigeria                    74 523       110 449      158 259     50.3       50.2        49.9           71.4              61.1    50.2
Saint Helena                      5             5            4   60.0       60.0        50.0           60.0              60.0    75.0
Senegal                     5 636          8 660      12 861     49.4       50.1        50.4           64.2              60.2    57.1
Sierra Leone                3 261          3 989       5 836     51.4       51.5        51.3           70.9              65.8    61.6
Togo                        2 785          4 432       6 780     50.7       50.6        50.5           75.3              66.8    56.6


ASIA EXCLUDING JAPAN     2 450 128    3 322 591     4 039 744    48.6       48.7        48.7           64.9              57.4    50.7


Central Asia                             53 399       61 349                50.8        50.9                             57.0    57.7
Kazakhstan                               15 926       15 753                51.7        52.4                             44.1    41.5
Kyrgyzstan                                 4 592       5 550                50.8        50.6                             63.7    63.4
Tajikistan                                 5 775       7 075                50.0        50.6                             71.1    73.5
Turkmenistan                               4 187       5 177                50.6        50.7                             54.7    50.5
Uzbekistan                               22 919       27 794                50.4        50.3                             61.6    63.1
92                  TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A1 (cont.)

                                                                                         Population
                                                   Total                                Female share                  Rural share
                                                (Thousands)                              (% of total)                 (% of total)

                                     1980          1995          2010            1980       1995        2010   1980      1995        2010


Eastern Asia excluding
                                   1 042 581     1 286 233     1 436 956         48.6       48.4        48.2   78.0      66.2        53.2
Japan
China(A)                             986 220     1 217 595     1 361 763         48.5       48.3        48.1   80.0      68.3        54.8
China, Hong Kong SAR                    5 039        6 214         7 069         47.9       50.3        52.6    8.5        0.0        0.0
China, Macao SAR                          252          412           548         49.2       51.7        52.4    1.6        0.0        0.0
China, mainland                      963 123     1 189 612     1 330 840         49.4       49.2        48.9   81.8      69.9        56.0
Democratic People’s
                                      17 239        21 717        23 991         51.3       50.9        50.6   43.1      40.9        36.6
Republic of Korea
Mongolia                                1 663        2 270         2 701         49.9       50.0        50.6   47.9      43.2        42.5
Republic of Korea                     37 459        44 651        48 501         49.9       49.9        50.5   43.3      21.8        18.1


Southeastern Asia                    355 774       479 834       589 616         50.2       50.2        50.2   74.5      64.7        51.8
Brunei Darussalam                         193          295           407         46.6       47.5        48.4   39.9      31.5        24.3
Cambodia                                6 748       11 380        15 053         53.7       51.9        51.0   91.0      85.8        77.2
Indonesia                            146 582       191 501       232 517         49.9       49.9        50.1   77.9      64.4        46.3
Lao People’s Democratic
                                        3 238        4 809         6 436         50.3       50.0        50.1   87.6      82.6        66.8
Republic
Malaysia                              13 763        20 594        27 914         49.7       49.2        49.2   58.0      44.3        27.8
Myanmar                               33 561        43 864        50 496         50.6       50.7        51.2   76.0      73.9        66.1
Philippines                           48 112        69 965        93 617         49.6       49.6        49.6   62.5      46.0        33.6
Singapore                               2 415        3 480         4 837         48.9       49.7        49.8    0.0        0.0        0.0
Thailand                              47 264        60 140        68 139         49.9       50.5        50.8   73.2      69.7        66.0
Timor-Leste                               581          849         1 171         49.1       48.6        49.1   83.6      77.4        71.9
Viet Nam                              53 317        72 957        89 029         51.5       51.3        50.6   80.8      77.8        71.2


Southern Asia                        949 618     1 332 534     1 719 122         48.0       48.3        48.6   76.6      72.3        68.1
Afghanistan                           13 946        18 084        29 117         48.1       48.2        48.2   84.3      80.2        75.2
Bangladesh                            90 397       128 086       164 425         48.5       49.2        49.4   85.1      78.3        71.9
Bhutan                                    423          509           708         48.2       49.1        47.3   89.8      79.4        63.1
India                                692 637       953 148     1 214 464         48.0       48.1        48.4   76.9      73.4        69.9
Iran (Islamic Republic of)            39 330        62 205        75 078         48.8       49.1        49.2   50.3      39.8        30.5
Maldives                                  158          248           314         47.5       48.8        49.4   77.8      74.2        59.6
Nepal                                 15 058        21 624        29 853         48.7       49.9        50.3   93.9      89.1        81.8
Pakistan                              82 609       130 397       184 753         47.4       48.2        48.5   71.9      68.2        63.0
Sri Lanka                             15 060        18 233        20 410         49.0       49.8        50.8   81.2      83.6        84.9


Western Asia                         102 155       170 591       232 701         48.8       48.7        48.6   48.6      37.6        33.7
Armenia                                              3 223         3 090                    52.6        53.4             33.7        36.3
Azerbaijan                                           7 784         8 934                    51.1        51.1             47.8        47.8
Bahrain                                   347          578           807         41.8       41.7        42.6   13.8      11.6        11.4
Cyprus                                    611          731           880         50.1       50.1        51.3   41.4      32.0        29.8
Georgia                                              5 069         4 219                    52.5        53.0             46.1        47.0
Iraq                                  14 024        20 971        31 467         49.0       49.8        49.4   34.5      31.2        33.6
Israel                                  3 764        5 374         7 285         50.0       50.7        50.4   11.4        9.1        8.3
S t a t is t ic a l a n n ex

                                                                                                                                     93
TABLE A1 (cont.)

                                                                             Population
                                             Total                          Female share                            Rural share
                                           (Thousands)                       (% of total)                             (% of total)

                               1980           1995        2010       1980       1995        2010           1980          1995        2010


Jordan                           2 225          4 304       6 472    48.3       47.7        48.7           40.0              21.8    21.5
Kuwait                           1 375          1 725       3 051    42.7       39.9        40.6             5.2              1.9     1.6
Lebanon                          2 785          3 491       4 255    50.4       50.8        51.0           26.3              15.2    12.8
Occupied Palestinian
                                 1 476          2 617       4 409    48.4       49.3        49.1           37.5              29.6    27.9
Territory (A)
Oman                             1 187          2 172       2 905    47.3       41.0        43.7           52.5              28.3    28.3
Qatar                             229            526        1 508    36.2       34.0        24.6           10.5               5.9     4.2
Saudi Arabia                     9 604        18 255       26 246    46.0       44.2        45.3           34.1              21.3    17.9
Syrian Arab Republic             8 971        14 610       22 505    49.6       49.6        49.5           53.3              49.9    45.1
Turkey                          46 161        61 206       75 705    49.5       49.6        49.8           56.2              37.9    30.4
United Arab Emirates             1 015          2 432       4 707    30.9       33.9        32.9           19.3              21.6    21.9
Yemen                            8 381        15 523       24 256    50.1       49.3        49.4           83.5              76.2    68.2


LATIN AMERICA
                               362 654       482 265      588 647    50.1       50.4        50.6           35.1              27.0    20.7
AND THE CARIBBEAN


Caribbean                       29 860        36 640       42 311    50.1       50.3        50.5           48.3              41.0    33.2
Anguilla                               7             10       15     42.9       50.0        53.3             0.0              0.0     0.0
Antigua and Barbuda                   72             68       89     51.4       51.5        50.6           65.3              66.2    69.7
Aruba                                 61             80      107     50.8       51.3        52.3           49.2              51.3    53.3
Bahamas                           210            281         346     50.5       50.5        51.2           27.1              19.2    15.9
Barbados                          249            258         257     52.2       51.9        51.4           60.2              65.5    59.1
British Virgin Islands                11             18       23     54.5       50.0        52.2           81.8              61.1    60.9
Cayman Islands                        17             33       57     52.9       51.5        50.9             0.0              0.0     0.0
Cuba                             9 835        10 910       11 204    49.4       49.8        49.9           31.9              25.7    24.3
Dominica                              73             69       67     50.7       50.7        50.7           37.0              30.4    25.4
Dominican Republic               5 927          8 124      10 225    49.4       49.6        49.8           48.7              42.2    29.5
Grenada                               89         100         104     51.7       51.0        50.0           67.4              69.0    69.2
Guadeloupe                        327            405         467     51.1       51.4        52.0             2.1              1.5     1.7
Haiti                            5 691          7 861      10 188    50.8       50.6        50.6           79.5              67.4    50.4
Jamaica                          2 133          2 466       2 730    50.7       50.7        51.1           53.3              49.4    46.3
Martinique                        326            370         406     51.5       52.2        53.2           20.2               2.2     2.0
Montserrat                            12             10          6   50.0       50.0        50.0           83.3              90.0    83.3
Netherlands Antilles              174            191         201     51.7       52.4        53.7           19.0              12.0     7.0
Puerto Rico                      3 197          3 701       3 998    51.3       51.7        52.1           33.1              12.9     1.2
Saint Kitts and Nevis                 43             43       52     51.2       51.2        51.9           65.1              67.4    67.3
Saint Lucia                       118            147         174     50.8       51.0        51.1           73.7              70.7    71.8
Saint Vincent
                                  100            108         109     52.0       50.0        49.5           73.0              57.4    52.3
and the Grenadines
Trinidad and Tobago              1 082         1 265        1 344    50.0       50.9        51.4           89.1              90.4    86.1
Turks and Caicos Islands               8             15       33     50.0       53.3        51.5           37.5              20.0     6.1
United States Virgin Islands          98         107         109     52.0       52.3        53.2           20.4               9.3     4.6
 
94                  TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A1 (cont.)

                                                                                         Population
                                                   Total                                Female share                  Rural share
                                                 (Thousands)                             (% of total)                 (% of total)

                                     1980           1995         2010            1980       1995        2010   1980      1995        2010


Central America                       91 879       124 004       153 115         50.1       50.4        50.8   39.8      32.9        28.3
Belize                                    144          220           313         49.3       49.5        49.5   50.7      52.7        47.3
Costa Rica                              2 349         3 479        4 640         49.0       49.2        49.2   56.9      44.2        35.7
El Salvador                             4 663         5 728        6 194         50.8       51.6        52.9   55.9      46.0        38.7
Guatemala                               7 016       10 007        14 377         49.4       50.3        51.3   62.6      56.9        50.5
Honduras                                3 634         5 588        7 616         49.8       49.9        50.0   65.1      57.7        51.2
Mexico                                68 872        91 650       110 645         50.2       50.5        50.8   33.7      26.6        22.2
Nicaragua                               3 250         4 659        5 822         49.9       50.2        50.5   50.1      46.5        42.7
Panama                                  1 951         2 673        3 508         49.2       49.5        49.6   49.6      40.0        25.2


South America                        240 915       321 621       393 221         50.1       50.4        50.6   31.6      23.0        16.4
Argentina                             28 154        34 772        40 666         50.6       50.9        50.9   17.1      11.3         7.6
Bolivia (Plurinational
                                        5 356         7 484       10 031         50.7       50.3        50.1   54.6      40.6        33.5
State of)
Brazil                               121 618       161 692       195 423         50.1       50.5        50.8   32.6      22.2        13.5
Chile                                 11 181        14 410        17 135         50.7       50.6        50.5   18.8      15.6        11.0
Colombia                              26 891        36 459        46 300         50.2       50.6        50.8   37.9      29.5        24.9
Ecuador                                 7 964       11 407        13 775         49.7       49.8        49.9   53.0      42.2        33.1
Falkland Islands (Malvinas)                  2              2           3        50.0       50.0        66.7   50.0        0.0        0.0
French Guiana                               68         139           231         48.5       48.2        50.2   29.4      25.2        23.8
Guyana                                    776          759           761         50.5       51.4        48.6   69.5      70.9        71.6
Paraguay                                3 199         4 802        6 460         49.6       49.4        49.5   58.3      47.9        38.5
Peru                                  17 328        23 943        29 496         49.7       49.8        49.9   35.4      29.7        28.4
Suriname                                  366          436           524         49.5       49.3        50.0   45.1      29.8        24.4
Uruguay                                 2 916         3 224        3 372         51.0       51.6        51.7   14.6        9.5        7.4
Venezuela (Bolivarian
                                      15 096        22 092        29 044         49.4       49.6        49.8   20.8      13.2         6.0
Republic of)


OCEANIA EXCLUDING
AUSTRALIA AND                           4 969         7 249       10 022         47.5       48.7        49.2   78.2      75.9        76.8
NEW ZEALAND
American Samoa                              33             53         69         48.5       49.1        49.3   24.2      15.1         7.2
Cook Islands                                18             19         20         50.0       47.4        50.0   44.4      42.1        25.0
Fiji                                      634          768           854         49.4       49.2        49.3   62.1      54.6        46.6
French Polynesia                          151          216           272         47.7       48.1        48.9   42.4      46.3        48.5
Guam                                      107          146           180         47.7       47.9        48.9    6.5        8.2        6.7
Kiribati                                    55             77        100         49.1       49.4        52.0   67.3      63.6        56.0
Marshall Islands                                           51         63                    49.0        52.4             33.3        28.6
Micronesia (Federated
                                                       107           111                    48.6        48.6             74.8        77.5
States of)
Nauru                                       7              10         10         57.1       50.0        50.0    0.0        0.0        0.0
New Caledonia                             143          193           254         48.3       48.7        50.0   42.7      39.9        34.6
Niue                                        3               2           1        66.7       50.0        100     100      50.0        100
Northern Mariana Islands                                   58         88                    50.0        52.3             10.3         9.1
Palau                                                      17         21                    47.1        52.4             29.4        19.0
S t a t is t ic a l a n n ex

                                                                                                                                     95
TABLE A1 (cont.)

                                                                             Population
                                           Total                            Female share                            Rural share
                                         (Thousands)                         (% of total)                             (% of total)

                             1980           1995          2010       1980       1995        2010           1980          1995        2010


Papua New Guinea               3 199          4 709        6 888     46.8       48.7        49.2           87.0              85.9    87.5
Samoa                            155           168           179     49.0       48.2        48.0           78.7              78.6    76.5
Solomon Islands                  229           362           536     48.0       48.1        48.1           89.5              85.4    81.3
Tokelau                              2              1            1   50.0        100        100             100              100     100
Tonga                               97             97        104     49.5       49.5        49.0           78.4              77.3    75.0
Tuvalu                               8              9         10     50.0       55.6        50.0           75.0              55.6    50.0
Vanuatu                          117           172           246     47.0       48.8        48.8           85.5              79.7    74.4
Wallis and Futuna Islands           11             14         15     54.5       50.0        53.3            100              100     100


COUNTRIES IN DEVELOPED
                            1 127 965    1 174 680      1 237 229    51.7       51.5        51.4           32.1              27.8    24.9
REGIONS


ASIA AND OCEANIA             134 636       147 245       152 810     50.7       50.9        51.1           37.0              32.2    29.5
Australia                     14 695        18 118        21 512     50.1       50.3        50.3           14.2              13.9    10.9
Japan                        116 794       125 442       126 995     50.8       51.0        51.3           40.4              35.4    33.2
New Zealand                    3 147          3 685        4 303     50.3       50.6        50.6           16.6              14.7    13.2


EUROPE                       739 232       727 362       732 760     52.1       51.9        51.9           33.2              29.0    27.4


Eastern Europe               369 928       309 805       291 485     52.8       52.6        53.1           39.2              31.8    31.6
Belarus                                     10 270         9 588                53.1        53.5                             32.1    25.7
Bulgaria                       8 862          8 357        7 497     50.2       51.0        51.7           37.9              32.2    28.3
Czech Republic                              10 319        10 411                51.4        50.9                             25.4    26.5
Czechoslovakia (A)            15 260                                 51.3                                  32.5
Hungary                       10 707        10 332         9 973     51.6       52.2        52.5           35.8              34.8    31.7
Poland                        35 574        38 595        38 038     51.3       51.3        51.8           41.9              38.5    38.8
Republic of Moldova                           4 339        3 576                52.2        52.5                             53.7    58.8
Romania                       22 201        22 681        21 190     50.7       51.0        51.4           53.9              46.0    45.4
Russian Federation                         148 497       140 367                53.1        53.8                             26.6    27.2
Slovakia                                      5 352        5 412                51.3        51.5                             43.4    43.2
Ukraine                                     51 063        45 433                53.6        53.9                             33.0    31.9
USSR (A)                     265 407                                 53.4                                  37.4
Yugoslav SFR (A)              11 917                                 51.0                                  54.5


Northern Europe               82 479        93 260        98 907     51.1       51.3        50.9           16.8              17.0    15.6
Denmark                        5 123          5 228        5 481     50.6       50.7        50.4           16.3              15.0    12.8
Estonia                                       1 439        1 339                53.6        53.9                             30.0    30.5
Faroe Islands                       43             43         50     51.2       51.2        50.0           69.8              69.8    58.0
Finland                        4 780          5 108        5 346     51.7       51.3        51.0           40.2              38.6    36.1
Iceland                          228           267           329     49.6       49.8        48.6           11.8               8.2     7.6
Ireland                        3 401          3 609        4 589     49.7       50.3        49.9           44.7              42.1    38.1
Latvia                                        2 492        2 240                53.9        53.9                             31.3    31.8
Lithuania                                     3 630        3 255                52.9        53.2                             32.7    32.8
96                TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A1 (cont.)

                                                                                        Population
                                                 Total                                 Female share                  Rural share
                                               (Thousands)                              (% of total)                 (% of total)

                                   1980           1995         2010            1980        1995        2010   1980      1995        2010


Norway                                4 086         4 359        4 855         50.4        50.6        50.3   29.4      26.2        22.4
Sweden                                8 310         8 827        9 293         50.5        50.6        50.3   16.9      16.2        15.3
United Kingdom                      56 508        58 258        62 130         51.3        51.4        50.9   12.2      11.2        10.1


Southern Europe                    116 325       143 699       153 780         51.2        51.2        51.0   34.8      35.3        32.5
Albania                               2 671         3 134        3 169         48.4        49.6        50.7   66.2      61.1        52.0
Andorra                                   37             65          87        48.6        47.7        48.3    8.1        6.2       11.5
Bosnia and Herzegovina                              3 332        3 760                     51.5        51.9             58.9        51.4
Croatia                                             4 669        4 410                     51.8        51.8             45.1        42.2
Gibraltar                                 28             29          31        46.4        48.3        48.4    0.0        0.0        0.0
Greece                                9 643       10 672        11 183         50.9        50.6        50.4   42.3      40.7        38.6
Holy See                                   1              1           1          0.0         0.0        0.0    0.0        0.0        0.0
Italy                               56 307        57 207        60 098         51.5        51.6        51.3   33.4      33.1        31.6
Malta                                   324          378           410         51.2        50.5        50.2   10.2        9.0        5.4
Montenegro                                                         626                                 50.8                         40.4
Portugal                              9 766       10 038        10 732         51.9        51.8        51.6   57.2      48.9        39.3
San Marino                                21             26         32         47.6        46.2        46.9   19.0        7.7        6.3
Serbia (A)                                                       9 856                                 50.5                         47.6
Serbia and Montenegro (A)                         10 828                                   50.4                         49.0
Slovenia                                            1 966        2 025                     51.4        51.2             49.4        52.0
Spain                               37 527        39 391        45 317         51.0        51.0        50.7   27.2      24.1        22.6
The former Yugoslav
                                                    1 963        2 043                     50.0        50.1             39.7        32.1
Republic of Macedonia


Western Europe                     170 500       180 598       188 588         51.8        51.3        51.1   27.3      25.2        23.0
Austria                               7 549         7 936        8 387         52.7        51.8        51.2   34.6      34.2        32.4
Belgium                                                         10 698                                 51.0                          2.6
Belgium-Luxembourg   (A)
                                    10 192        10 493                       51.1        51.1                5.2        3.8
France                              53 950        57 999        62 637         51.2        51.4        51.4   26.7      25.1        22.2
Germany                             78 289        81 622        82 057         52.4        51.4        50.9   27.2      26.7        26.2
Liechtenstein                             25             31          36        52.0        51.6        52.8   84.0      83.9        86.1
Luxembourg                                                         492                                 50.4                         17.7
Monaco                                    26             31          33        53.8        51.6        51.5    0.0        0.0        0.0
Netherlands                         14 150        15 448        16 653         50.4        50.6        50.4   35.3      27.2        17.1
Switzerland                           6 319         7 038        7 595         51.4        51.2        51.2   42.9      26.4        26.4


NORTHERN AMERICA                   254 097       300 073       351 659         50.9        50.9        50.6   26.1      22.7        17.9
Bermuda                                   56             61         65         48.2        49.2        49.2    0.0        0.0        0.0
Canada                              24 516        29 302        33 890         50.2        50.5        50.5   24.3      22.3        19.4
Greenland                                 50             56         57         48.0        48.2        49.1   24.0      19.6        15.8
Saint Pierre and Miquelon                 6              6            6        50.0        50.0        50.0   16.7      16.7        16.7
United States of America           229 469       270 648       317 641         51.0        50.9        50.6   26.3      22.7        17.7
S t a t is t ic a l a n n ex

                                                                                                                97
TABLE A2
Female share of national, rural and urban population aged 15–49, most recent and earliest observations

                                            Most recent observation                      Earliest observation
                                                  (1999–2008)                                 (1960–1980)
                                                      (%)                                          (%)

                                      National       Rural        Urban      National             Rural         Urban


WORLD


COUNTRIES IN DEVELOPING REGIONS


AFRICA


Sub-Saharan Africa


Eastern Africa
Burundi                                    ..           ..              ..      50.1               50.2         46.2
Comoros                                    ..           ..              ..      52.2               52.6         51.0
Djibouti                                   ..           ..              ..          ..                ..           ..
Eritrea                                                 ..              ..
Ethiopia                                50.0         49.9         50.5
Ethiopia PDR                                                                        ..                ..           ..
Kenya                                   50.9         54.3         38.9          51.1               53.2         37.6
Madagascar                                 ..           ..              ..      51.6               51.5         51.8
Malawi                                  51.4         52.1         48.7          53.3               54.5         42.6
Mauritius                               49.7         49.6         49.9              ..                ..           ..
Mozambique                                 ..           ..              ..          ..                ..           ..
Réunion                                    ..           ..              ..          ..                ..           ..
Rwanda                                  52.9         55.0         44.3          52.3               53.1         40.8
Seychelles                                 ..           ..              ..      51.7               50.6         54.8
Somalia                                 50.5         50.1         51.2              ..                ..           ..
Uganda                                  52.3         52.5         51.5          50.2               51.1         42.3
United Republic of Tanzania                ..           ..              ..      52.4               53.7         45.9
Zambia                                  51.7          52.4        50.5          53.1               56.8         47.9
Zimbabwe                                52.3          53.2        50.9              ..                ..           ..


Middle Africa
Angola                                     ..           ..              ..          ..                ..           ..
Cameroon                                   ..           ..              ..      53.3               56.0         47.3
Central African Republic                   ..           ..              ..      54.5               55.2         53.1
Chad                                       ..           ..              ..          ..                ..           ..
Congo                                      ..           ..              ..          ..                ..           ..
Democratic Republic of the Congo           ..           ..              ..          ..                ..           ..
Equatorial Guinea                          ..           ..              ..          ..                ..           ..
Gabon                                      ..           ..              ..          ..                ..           ..
Sao Tome and Principe                   51.4          49.5            52.8          ..                ..           ..


Northern Africa                                                                 49.3               50.7         47.1
Algeria                                    ..           ..              ..      50.7               50.8         50.5
98                TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A2 (cont.)

                                                               Most recent observation                     Earliest observation
                                                                       (1999–2008)                             (1960–1980)
                                                                            (%)                                    (%)

                                                       National            Rural      Urban     National          Rural           Urban


Egypt                                                         ..               ..          ..     50.5             51.2           49.3
Libyan Arab Jamahiriya                                    49.5              49.9      49.5        48.2             49.5           47.2
Morocco                                                   51.2              51.0      51.4        51.8             52.2           51.0
Sudan                                                         ..               ..          ..     51.4             53.7           45.1
Tunisia                                                       ..               ..          ..     50.3             51.8           48.4
Western Sahara                                                ..               ..          ..     42.4             45.4           38.5


Southern Africa                                           51.7              51.7      52.3        50.1             53.5           43.3
Botswana                                                  52.4              50.9      53.2        52.5             52.6           47.5
Lesotho                                                   50.8              49.2      54.9           ..              ..              ..
Namibia                                                   51.6              52.6      50.1        48.7             52.3           39.2
South Africa                                              52.0              54.0      50.7        49.0             55.6           43.2
Swaziland                                                     ..               ..          ..        ..              ..              ..


Western Africa
Benin                                                     54.0              55.7      51.8        57.4             59.1           55.0
Burkina Faso                                              54.2              55.9      49.7        52.7             53.0           48.9
Cape Verde                                                51.4              52.5      50.6           ..              ..              ..
Côte d’Ivoire                                                 ..               ..          ..     48.7             51.7           43.4
Gambia                                                        ..               ..          ..        ..               ..             ..
Ghana                                                     51.3              51.1      51.4           ..               ..             ..
Guinea                                                        ..               ..          ..        ..               ..             ..
Guinea-Bissau                                                 ..               ..          ..        ..               ..             ..
Liberia                                                       ..               ..          ..     52.2             54.9           46.3
Mali                                                          ..               ..          ..        ..               ..             ..
Mauritania                                                    ..               ..          ..        ..               ..             ..
Niger                                                     51.3              51.6      50.0           ..               ..             ..
Nigeria                                                       ..               ..          ..     51.3             52.6           45.2
Saint Helena                                                  ..               ..          ..        ..               ..             ..
Senegal                                                   53.7              54.4         53.0     52.6             53.0           51.8
Sierra Leone                                                  ..               ..          ..        ..               ..             ..
Togo                                                          ..               ..          ..        ..               ..             ..


ASIA EXCLUDING JAPAN                                      49.5              49.2         49.5


Central Asia                                              50.2              49.5         51.0     49.8             50.0           49.6
Kazakhstan                                                50.6              48.5         52.3     49.8             48.5           50.8
Kyrgyzstan                                                50.1              49.0         52.0     49.8             49.6           50.2
Tajikistan                                                50.1              50.3         49.5     50.0             50.7           48.8
Turkmenistan                                                  ..               ..          ..     49.7             50.5           48.8
Uzbekistan                                                50.2              50.3         50.0     49.9             50.4           49.2


Eastern Asia excluding Japan                              49.3              47.8         49.9
China                                                     48.7              48.6         48.8        ..               ..             ..
S t a t is t ic a l a n n ex

                                                                                                                  99
TABLE A2 (cont.)

                                              Most recent observation                      Earliest observation
                                                    (1999–2008)                                 (1960–1980)
                                                        (%)                                          (%)

                                        National       Rural        Urban      National             Rural         Urban


China, Hong Kong SAR                         ..           ..              ..          ..                ..           ..
China, Macao SAR                             ..           ..              ..      50.7               48.4         50.8
China, mainland                              ..           ..              ..          ..                ..           ..
Democratic People’s Republic of Korea        ..           ..              ..          ..                ..           ..
Mongolia                                  50.3         48.5         51.4              ..                ..           ..
Republic of Korea                         49.1         46.4         49.6          50.3               50.2         50.4


Southeastern Asia                         50.2         49.7         50.7
Brunei Darussalam                         49.8         47.8         50.5          47.1               50.0         43.9
Cambodia                                  51.1         50.9         51.9          50.5               50.7         48.5
Indonesia                                 50.3         50.1         50.5          52.7               52.7         53.0
Lao People’s Democratic Republic          50.4         50.6         50.0              ..                ..           ..
Malaysia                                  49.2         48.6         49.5              ..                ..           ..
Myanmar                                      ..           ..              ..          ..                ..           ..
Philippines                                  ..           ..              ..      51.3               50.3         53.1
Singapore                                    ..           ..              ..          ..                ..           ..
Thailand                                  50.4         50.0         51.5          50.5               50.5         50.7
Timor-Leste                                  ..           ..              ..          ..                ..           ..
Viet Nam                                  50.2          49.8        51.2              ..                ..           ..


Southern Asia                             49.4          49.9        47.9          48.7               49.4         44.9
Afghanistan                                  ..           ..              ..      49.2               49.3         48.3
Bangladesh                                50.0          51.4        46.2          48.4               49.4         39.5
Bhutan                                    46.1          47.2        44.2              ..                ..           ..
India                                     48.2          48.7        47.0          48.4               49.5         43.9
Iran (Islamic Republic of)                49.3          49.2        49.3          48.7               49.7         47.1
Maldives                                  50.8          50.6            51.1      46.5               46.3         48.5
Nepal                                     50.9          51.6            48.2      51.5               51.8         45.6
Pakistan                                  49.6          50.2            48.7      47.7               48.9         40.9
Sri Lanka                                 50.2          50.5            48.6      48.9               49.9         45.4


Western Asia                              48.9          48.5            49.1      47.2               48.5         46.0
Armenia                                   50.7          49.2            51.6      50.7               49.8         51.1
Azerbaijan                                50.3          49.8            50.7      50.2               52.1         48.9
Bahrain                                      ..           ..              ..      43.4               49.2         42.0
Cyprus                                    50.8          49.2            51.5      52.0               53.0         50.4
Georgia                                   51.7          49.7            53.5      51.5               50.4         52.4
Iraq                                      49.8          50.3            49.6      49.9               51.4         48.3
Israel                                    49.8          48.7            49.9      50.2               48.6         50.5
Jordan                                    48.2          48.0            48.3      48.4               49.0         47.9
Kuwait                                       ..           ..              ..          ..                ..           ..
Lebanon                                      ..           ..              ..      49.5               50.0         49.2
Occupied Palestinian Territory               ..           ..              ..
Oman                                      38.5          40.3            37.9          ..                ..           ..
100                 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A2 (cont.)

                                                                 Most recent observation                     Earliest observation
                                                                         (1999–2008)                             (1960–1980)
                                                                              (%)                                    (%)

                                                         National            Rural      Urban     National          Rural           Urban


Qatar                                                           ..               ..          ..        ..              ..              ..
Saudi Arabia                                                    ..               ..          ..        ..              ..              ..
Syrian Arab Republic                                        50.0              50.3      49.9        49.5             50.5           47.9
Turkey                                                      49.1              49.9      48.7        48.5             51.4           42.0
United Arab Emirates                                            ..               ..          ..     22.5             26.8           21.8
Yemen                                                           ..               ..          ..        ..              ..              ..


LATIN AMERICA AND THE CARIBBEAN                             50.7              48.3      51.8        50.9             48.6           53.3


Caribbean
Anguilla                                                        ..               ..          ..        ..              ..              ..
Antigua and Barbuda                                             ..               ..          ..     53.5             52.4           55.0
Aruba                                                           ..               ..          ..        ..              ..              ..
Bahamas                                                         ..               ..          ..        ..              ..              ..
Barbados                                                        ..               ..          ..        ..              ..              ..
British Virgin Islands                                          ..               ..          ..        ..              ..              ..
Cayman Islands                                                  ..               ..          ..        ..              ..              ..
Cuba                                                        49.3              47.7      49.8        49.2             46.7           50.7
Dominica                                                        ..               ..          ..        ..              ..              ..
Dominican Republic                                          50.4              49.5      50.8        50.7             48.3           55.5
Grenada                                                         ..               ..          ..        ..               ..             ..
Guadeloupe                                                      ..               ..          ..        ..               ..             ..
Haiti                                                       51.2              47.7      56.6           ..               ..             ..
Jamaica                                                     51.3              48.9      53.3        53.4             51.9           56.2
Martinique                                                      ..               ..          ..        ..               ..             ..
Montserrat                                                      ..               ..          ..        ..               ..             ..
Netherlands Antilles                                            ..               ..          ..     50.5             50.8           51.4
Puerto Rico                                                     ..               ..          ..     52.5             51.8           52.9
Saint Kitts and Nevis                                           ..               ..          ..     55.1             54.6           56.2
Saint Lucia                                                 50.9              51.0         50.6        ..               ..             ..
Saint Vincent and the Grenadines                                ..               ..          ..        ..               ..             ..
Trinidad and Tobago                                             ..               ..          ..        ..               ..             ..
Turks and Caicos Islands                                        ..               ..          ..        ..               ..             ..
United States Virgin Islands                                    ..               ..          ..     49.3             46.4           51.5


Central America                                             51.6              50.2         52.7     50.9             48.4           54.2
Belize                                                      51.4              50.5         52.2     51.5             46.4           55.7
Costa Rica                                                  51.1              50.0         51.9     50.4             47.7           53.9
El Salvador                                                 54.1              53.2         54.6     52.1             49.9           55.3
Guatemala                                                   52.7              51.9         53.3     49.7             48.2           52.4
Honduras                                                    51.0              48.4         53.2     51.3             50.3           54.2
Mexico                                                      52.2              52.3         52.2     51.2             49.5           52.7
Nicaragua                                                   50.9              48.6         52.6     51.9             48.6           56.6
Panama                                                      49.7              46.9         51.6     49.5             46.6           53.0
S t a t is t ic a l a n n ex

                                                                                                           101
TABLE A2 (cont.)

                                           Most recent observation                      Earliest observation
                                                 (1999–2008)                                 (1960–1980)
                                                     (%)                                          (%)

                                     National       Rural        Urban      National             Rural         Urban


South America                          50.1         46.8         51.1          50.2               47.3         52.2
Argentina                              49.9         47.0         50.2          50.3               45.4         51.2
Bolivia (Plurinational State of)       50.1         46.8         51.6          51.2               50.5         52.0
Brazil                                 50.8         46.8         51.6          50.9               49.0         52.9
Chile                                  49.8         46.2         50.3          51.6               45.3         54.1
Colombia                               51.5         47.0         52.7          52.0               48.3         55.2
Ecuador                                49.8         48.4         50.4          50.8               49.3         53.5
Falkland Islands (Malvinas)               ..           ..              ..      42.1               40.1         44.2
French Guiana                             ..           ..              ..          ..                ..           ..
Guyana                                 50.1         49.0         52.6          50.5               49.7         54.5
Paraguay                               49.4         46.1         51.7          52.1               50.7         54.3
Peru                                   50.7         48.0         51.4          50.5               50.9         50.0
Suriname                               49.2         48.3         49.6              ..                ..           ..
Uruguay                                50.3         43.4         50.8          50.7               41.7         52.6
Venezuela (Bolivarian Republic of)     49.8         44.7         50.4              ..                ..           ..


OCEANIA EXCLUDING AUSTRALIA AND
NEW ZEALAND
American Samoa                            ..           ..              ..          ..                ..           ..
Cook Islands                              ..           ..              ..          ..                ..           ..
Fiji                                   48.8          47.4        50.0          49.6               49.8         49.2
French Polynesia                          ..           ..              ..          ..                ..           ..
Guam                                      ..           ..              ..          ..                ..           ..
Kiribati                               51.0          49.9        52.3          51.6               53.2         47.2
Marshall Islands                          ..           ..              ..          ..                ..           ..
Micronesia (Federated States of)          ..           ..              ..          ..                ..           ..
Nauru                                     ..           ..              ..          ..                ..           ..
New Caledonia                             ..           ..              ..          ..                ..           ..
Niue                                      ..           ..              ..          ..                ..           ..
Northern Mariana Islands               61.2          66.3            60.5          ..                ..           ..
Palau                                     ..           ..              ..          ..                ..           ..
Papua New Guinea                       49.1          49.8            45.4      47.6               49.2         39.3
Samoa                                     ..           ..              ..      48.6               48.4         49.6
Solomon Islands                           ..           ..              ..      48.2               50.2         29.9
Tokelau                                   ..           ..              ..          ..                ..           ..
Tonga                                  49.5          49.3            49.9          ..                ..           ..
Tuvalu                                    ..           ..              ..          ..                ..           ..
Vanuatu                                   ..           ..              ..      47.3               49.0         37.6
Wallis and Futuna Islands                 ..           ..              ..          ..                ..           ..


COUNTRIES IN DEVELOPED REGIONS         49.5          47.9            50.2


ASIA AND OCEANIA                       50.1          49.3            50.2      49.8               47.9         50.1
Australia                              49.8          48.9            50.0      48.7               44.8         49.5
102                  TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A2 (cont.)

                                                                  Most recent observation                     Earliest observation
                                                                          (1999–2008)                             (1960–1980)
                                                                               (%)                                    (%)

                                                          National            Rural      Urban     National          Rural           Urban


Japan                                                        49.4              49.5      49.4        51.4             52.4           50.9
New Zealand                                                  51.0              49.4      51.2        49.3             46.4           49.8


EUROPE                                                       49.5              47.7      50.4


Eastern Europe                                               49.7              47.9      50.6        51.5             51.4           51.4
Belarus                                                      50.2              47.0      51.1        52.6             52.9           52.2
Bulgaria                                                     49.2              46.9      50.0        49.7             49.7           49.6
Czech Republic                                               48.7              47.8      49.0
Czechoslovakia                                                                                          ..              ..              ..
Hungary                                                      49.4              47.8      50.2        51.6             51.7           51.4
Poland                                                       49.5              48.1      50.4        52.5             52.7           52.4
Republic of Moldova                                          50.3              48.9      52.0        51.9             51.3           52.7
Romania                                                      49.2              46.6      51.1        50.6             51.0           49.8
Russian Federation                                           50.6              48.9      51.2        50.2             48.1           51.0
Slovakia                                                     49.2              48.2      50.1           ..              ..              ..
Ukraine                                                      50.6              48.7      51.4        52.8             54.0           52.0
USSR                                                                                                    ..              ..              ..
Yugoslav SFR                                                                                            ..               ..             ..


Northern Europe                                              49.2              47.2      50.1        49.6             46.8           51.7
Denmark                                                          ..               ..          ..     50.1             45.7           51.5
Estonia                                                      50.3              48.0      51.4        50.1             47.4           51.1
Faroe Islands                                                46.4              45.7      47.6        46.4             44.6           50.4
Finland                                                      49.0              47.6      49.5        50.8             47.3           53.3
Iceland                                                      47.8              43.9      48.1        49.2             47.2           51.5
Ireland                                                      49.8              47.9      51.0        49.8             45.8           53.9
Latvia                                                       50.0              47.2         51.4     50.5             48.4           51.3
Lithuania                                                    50.2              47.2         51.6     50.7             48.9           51.6
Norway                                                       49.0              47.4         49.5     49.3             46.6           51.4
Sweden                                                           ..               ..          ..     49.5             45.7           50.7
United Kingdom                                               50.4              49.7         50.6        ..               ..             ..


Southern Europe                                              49.5              47.9         50.5
Albania                                                      50.9              50.2         51.7        ..               ..             ..
Andorra                                                          ..               ..          ..        ..               ..             ..
Bosnia and Herzegovina                                           ..               ..          ..        ..               ..             ..
Croatia                                                      49.6              47.6         51.1        ..               ..             ..
Gibraltar                                                        ..               ..          ..        ..               ..             ..
Greece                                                       49.1              45.3         50.1     51.4             52.7           50.7
Holy See                                                         ..               ..          ..        ..               ..             ..
Italy                                                            ..               ..          ..        ..               ..             ..
Malta                                                        48.9              47.4         48.9        ..               ..             ..
S t a t is t ic a l a n n ex

                                                                                                                103
TABLE A2 (cont.)

                                                  Most recent observation                    Earliest observation
                                                        (1999–2008)                               (1960–1980)
                                                            (%)                                        (%)

                                            National       Rural        Urban    National             Rural         Urban


Montenegro                                    49.8         47.3         51.2            ..                ..           ..
Portugal                                      50.2         49.6         51.2        51.9               51.2         54.0
San Marino                                       ..           ..            ..          ..                ..           ..
Serbia                                        49.8         47.7         51.1
Serbia and Montenegro                                                                   ..                ..           ..
Slovenia                                      48.4         47.9         48.8            ..                ..           ..
Spain                                         49.4         48.0         50.1        51.0               49.8         52.3
The former Yugoslav Republic of Macedonia        ..           ..            ..


Western Europe
Austria                                       49.5         48.3         50.1        50.7               49.6         51.7
Belgium                                       49.5         48.7         49.5            ..                ..           ..
Belgium-Luxembourg                               ..           ..            ..          ..                ..           ..
France                                        50.1         48.2         50.6        49.4               47.6         50.2
Germany                                          ..           ..            ..          ..                ..           ..
Liechtenstein                                    ..           ..            ..          ..                ..           ..
Luxembourg                                       ..           ..            ..      49.8               48.5         50.6
Monaco                                           ..           ..            ..          ..                ..           ..
Netherlands                                   49.5         49.0         49.8        49.2               48.1         49.6
Switzerland                                   49.5          48.8        49.7        49.6               48.2         50.7


NORTHERN AMERICA                              48.9          47.2        49.2        49.8               47.0         51.2
Bermuda                                          ..           ..            ..          ..                ..           ..
Canada                                        50.4          49.3        50.7        49.6               46.8         50.8
Greenland                                     46.5          43.2        47.1        48.8               45.4         51.0
Saint Pierre and Miquelon                        ..           ..            ..          ..                ..           ..
United States of America                      49.7          49.1        49.9        50.9               48.8         51.7
104                   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A3
Economically active population, female share of economically active population and agricultural share
of economically active women in 1980, 1995 and 2010

                                                                               Economically active population
                                                     Total                                Female share              Agricultural share of
                                                   (Thousands)                             (% of total)          economically active women
                                                                                                                            (%)

                                       1980           1995          2010           1980       1995        2010   1980      1995      2010


WORLD                                1 894 978     2 575 394      3 282 308        38.1       39.6        40.5    53.5      48.7     42.0


COUNTRIES IN DEVELOPING
                                     1 353 280     2 000 716      2 656 880        36.4       38.3        39.2    72.1      62.8     52.7
REGIONS


AFRICA                                 172 652       268 197       407 905         38.5       39.5        41.4    78.8      70.9     62.2


Sub-Saharan Africa                     147 699       227 175       346 919         41.8       42.4        43.8    79.1      72.7     65.0


Eastern Africa                          61 341        97 031       152 689         46.2       47.2        48.3    91.0      86.5     79.2
Burundi                                   1 977         2 978        4 260         53.2       52.3        51.4    97.8      97.6     97.3
Comoros                                     151          250           387         43.0       42.8        43.7    93.8      88.8     82.8
Djibouti                                    133          249           381         42.9       43.4        43.3    91.2      87.0     79.4
Eritrea                                                 1 200        2 086                    42.1        40.9              83.4     78.5
Ethiopia                                              24 306        41 929                    43.6        47.9              83.3     73.5
Ethiopia PDR    (A)
                                        14 833                                     41.1                           88.6
Kenya                                     6 718       12 139        18 887         45.7       46.3        46.4    88.1      82.9     73.9
Madagascar                                3 880         5 966       10 060         48.6       48.3        49.1    92.7      85.8     76.4
Malawi                                    2 876         4 302        6 542         51.6       50.2        49.8    96.1      95.1     94.0
Mauritius                                   370          485           589         29.7       33.0        37.0    27.3      11.3      5.5
Mozambique                                5 951         7 547       10 778         51.2       55.5        55.8    97.0      95.5     94.0
Réunion                                     170          270           362         35.3       43.3        46.4     8.3       0.9      0.6
Rwanda                                    2 328         2 327        4 722         52.6       52.7        53.1    98.0      97.3     96.1
Seychelles                                    28             33         40         46.4       48.5        47.5    92.3      81.3     78.9
Somalia                                   2 437         2 565        3 731         38.0       38.4        39.2    90.2      85.4     76.7
Uganda                                    5 679         9 225       14 896         47.5       47.7        47.8    90.8      86.2     77.5
United Republic of Tanzania               9 084       14 855        22 339         50.2       49.8        49.7    91.8      89.6     84.0
Zambia                                    1 985         3 481        5 146         36.3       42.9        43.3    84.7      79.7     68.0
Zimbabwe                                  2 741         4 853        5 554         46.8       46.7        44.2    84.5      78.2     68.2


Middle Africa                           21 068        33 670        50 767         42.7       42.0        41.8    85.4      79.9     70.2
Angola                                    3 421         5 397        8 447         45.7       45.6        47.3    87.3      84.4     80.6
Cameroon                                  3 402         5 086        7 622         43.2       40.1        41.7    86.5      77.3     54.1
Central African Republic                  1 018         1 476        2 030         46.6       45.8        44.9    90.3      83.9     70.3
Chad                                      1 547         2 790        4 623         25.9       45.8        49.0    95.3      88.3     76.2
Congo                                       700         1 099        1 524         40.3       42.1        40.6    80.5      63.3     44.4
Democratic Republic of
                                        10 558        17 137        25 488         43.8       40.5        38.5    83.7      79.1     72.6
the Congo
Equatorial Guinea                             87         174           268         33.3       32.8        32.5    93.1      89.5     87.4
Gabon                                       305          472           708         44.9       44.1        43.9    73.7      50.0     26.7
Sao Tome and Principe                         30             39         57         33.3       33.3        40.4    80.0      84.6     69.6
S t a t is t ic a l a n n ex

                                                                                                                               105
TABLE A3 (cont.)

                                                                  Economically active population
                                         Total                              Female share                     Agricultural share of
                                       (Thousands)                           (% of total)                 economically active women
                                                                                                                             (%)

                           1980           1995         2010         1980        1995        2010           1980          1995       2010


Northern Africa            31 554         50 078       74 694        20.4       23.9        28.3           78.2              58.5   42.8
Algeria                      4 555          9 018      14 950        21.4       25.6        34.0           69.3              51.0   32.9
Egypt                      11 780         18 531       27 492        16.9       22.1        25.7           82.7              55.3   39.3
Libyan Arab Jamahiriya        838           1 517       2 425        13.4       18.3        24.5           62.5              20.9    8.6
Morocco                     5 848           9 015      11 963        21.3       24.2        24.8           72.3              59.7   49.1
Sudan                       6 601           9 056      13 708        26.5       26.7        31.3           88.4              80.3   65.1
Tunisia                     1 865           2 829       3 886        19.0       23.4        27.4           52.7              37.3   24.6
Western Sahara                    67         112          270        31.3       33.9        38.5           76.2              57.9   42.3


Southern Africa            10 753         16 325       21 371        41.2       43.5        45.9           23.2              14.4    9.8
Botswana                      332            506          741        38.3       42.9        43.6           74.8              54.8   55.1
Lesotho                       538            720          895        50.7       51.5        52.3           64.1              57.1   50.6
Namibia                       309            507          769       47.2        45.4        46.8           63.7              47.8   31.9
South Africa                9 350         14 220       18 481       40.3        42.9        45.5           15.8               8.1    4.2
Swaziland                     224            372          485       48.7        49.5        49.7           63.3              47.8   31.5


Western Africa             47 936         71 093      108 384       38.0        37.7        39.6           70.3              60.2   50.7
Benin                       1 168           2 240       3 778       33.6        40.2        40.8           68.7              59.9   43.0
Burkina Faso                2 989           4 421       7 425       46.4        47.6        47.1           92.8              93.4   93.3
Cape Verde                        90         131          195       40.0        38.2        42.6           38.9              28.0   16.9
Côte d’Ivoire               3 096           5 407       8 106       30.4        29.2        30.5           75.0              65.9   45.0
Gambia                        273            483          806       46.2        45.5        46.8           92.9              90.5   86.5
Ghana                       4 473           7 247      11 116       49.5        49.2        49.0           56.8              53.4   49.3
Guinea                      2 210           3 535       4 968       47.5        46.9        47.1           96.4              90.3   84.3
Guinea-Bissau                 331            451          613       39.3        40.1        38.2           97.7              96.1   94.4
Liberia                       711            719        1 509       40.4        39.8        40.3           88.9              80.4   68.6
Mali                        1 963           2 508       3 517       35.0        34.6        38.4           92.3              86.2   73.6
Mauritania                    603            913        1 441       42.6        42.5        43.2           79.4              62.4   62.6
Niger                       1 965           3 045       5 228       33.7        32.3        31.3           97.6              97.4   97.0
Nigeria                    23 353         33 165       49 144       34.4        33.6        36.9           57.4              39.4   26.8
Saint Helena                      2              2            2     50.0        50.0        50.0          100.0               0.0    0.0
Senegal                     2 382           3 591       5 626       40.1        40.7        43.2           89.9              84.0   77.2
Sierra Leone                1 265           1 546       2 197       52.6        50.4        51.1           82.0              78.8   72.6
Togo                        1 062          1 689        2 713       39.8        38.3        38.1           66.9              62.9   57.8


ASIA EXCLUDING JAPAN     1 052 771     1 533 185     1 964 239      36.7        38.5        38.4           76.0              67.5   57.6


Central Asia                              21 059       29 095                   46.7        47.0                             25.0   17.8
Kazakhstan                                 7 773        8 427                   47.6        49.8                             12.6    6.8
Kyrgyzstan                                 1 885        2 547                   45.5        42.6                             23.9   14.6
Tajikistan                                 1 678        2 896                   46.7        46.8                             41.8   31.1
Turkmenistan                               1 635        2 437                   46.4        47.1                             39.3   33.4
106                 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A3 (cont.)

                                                                             Economically active population
                                                   Total                                 Female share              Agricultural share of
                                                 (Thousands)                              (% of total)          economically active women
                                                                                                                           (%)

                                     1980           1995         2010            1980        1995        2010   1980      1995      2010


Uzbekistan                                            8 088       12 788                     46.2        46.2              31.2     20.2


Eastern Asia excluding
                                     526 764       737 152       855 786         43.0        45.0        45.5    77.1      71.1     61.8
Japan
China (A)                            504 496       704 769       817 033         43.2        45.2        45.6    78.2      73.1     64.0
China, Hong Kong SAR                    2 415         3 086        3 759         33.8        39.0        47.4     1.2       0.5      0.1
China, Macao SAR
China, mainland
Democratic People’s
                                        7 103       10 400        12 979         39.7        41.1        44.8    52.0      37.0     23.9
Republic of Korea
Mongolia                                  574          862         1 204         46.5        46.3        50.2    36.0      26.6     17.1
Republic of Korea                     14 591        21 121        24 570         37.0        39.6        41.2    46.9      14.9      5.5


Southeastern Asia                    147 907       221 405       299 123         41.2        41.9        41.6    64.2      57.1     47.8
Brunei Darussalam                           71         131           195         23.9        35.9        43.6     5.9       0.0      0.0
Cambodia                                3 209         4 930        8 029         54.0        51.6        48.3    80.0      76.4     69.8
Indonesia                             55 181        84 276       115 905         34.9        37.8        36.9    55.8      53.4     44.2
Lao People’s Democratic
                                        1 463         2 172        3 281         49.8        50.0        50.3    82.3      80.2     77.8
Republic
Malaysia                                4 984         8 167       12 445         34.5        33.9        35.8    49.3      19.3      7.5
Myanmar                               15 972        22 769        29 464         44.9        45.2        46.3    80.3      75.8     70.0
Philippines                           17 861        28 019        39 967         38.4        37.1        38.8    37.0      28.1     20.9
Singapore                               1 117         1 740        2 637         34.6        38.7        42.1     1.3       0.1      0.0
Thailand                              23 709        33 490        39 198         46.9        45.5        46.5    74.2      60.8     47.1
Timor-Leste                               242          332           461         39.7        38.0        40.6    94.8      92.1     88.2
Viet Nam                              24 098        35 379        47 541         49.3        49.8        48.5    75.3      71.0     64.0


Southern Asia                        348 669       496 504       699 660         26.6        28.3        29.6    81.5      70.5     60.4
Afghanistan                             4 548         5 620        9 384         24.1        22.4        23.4    86.0      83.9     82.0
Bangladesh                            38 345        56 409        78 232         37.7        38.2        40.3    80.9      69.9     57.4
Bhutan                                    146          150           326         25.3        18.7        33.1    97.3      96.4     97.2
India                                259 177       364 665       491 326         26.8        28.2        28.6    82.6      71.5     61.8
Iran (Islamic Republic of)            11 064        18 288        30 746         19.7        24.9        30.2    50.0      40.1     33.3
Maldives                                    46             70        150         21.7        27.1        42.0    40.0      21.1     14.3
Nepal                                   5 837         8 061       12 936         33.7        40.2        45.7    98.0      98.0     97.8
Pakistan                              23 563        35 980        67 292           8.1       12.2        20.3    87.7      68.7     56.9
Sri Lanka                               5 943         7 261        9 268         31.3        33.0        38.2    58.0     48.6      41.6


Western Asia                          29 431        57 065        80 575         21.3        26.1        25.7    72.2     50.2      35.8
Armenia                                               1 375        1 575                     48.4        50.2               8.0      3.0
Azerbaijan                                            3 229        4 633                     47.3        47.9             33.1      25.6
Bahrain                                   136          263           384         11.0        18.3        21.6     0.0       0.0      0.0
Cyprus                                    282          343           446         31.9        38.5        45.7    36.7     11.4       4.9
Georgia                                              2 508         2 278                     47.1        46.7             20.5      11.7
Iraq                                    3 097        5 018         7 918         12.8        14.2        17.5    62.0     32.0      15.7
S t a t is t ic a l a n n ex

                                                                                                                                  107
TABLE A3 (cont.)

                                                                     Economically active population
                                             Total                             Female share                     Agricultural share of
                                           (Thousands)                          (% of total)                 economically active women
                                                                                                                                (%)

                               1980           1995        2010         1980        1995        2010           1980          1995       2010


Israel                           1 271          2 039       2 935       36.2       43.6        47.0             3.7              1.7    0.8
Jordan                            444           1 160       1 882       11.9       14.1        17.6           58.5              35.6   22.4
Kuwait                            457            823        1 541       14.2       21.5        24.7             0.0              0.0    0.0
Lebanon                           857           1 190       1 563       19.8       23.7        26.0           20.0               7.1    2.2
Occupied Palestinian
                                  465            866        1 508       26.0       26.3        26.0           57.9              36.0   22.2
Territory (A)
Oman                              341            778        1 123       17.3       12.5        20.4           25.4              17.5   10.5
Qatar                             106            284         976         9.4       13.0        11.0             0.0              0.0    0.0
Saudi Arabia                     2 415          5 752       9 570        9.9       11.2        16.0           25.1               7.6    1.8
Syrian Arab Republic             2 020          4 240       7 365       13.6       22.0        21.7           78.2              65.8   56.0
Turkey                          15 299        22 518       25 942       25.8       28.1        25.5           87.9              79.1   66.3
United Arab Emirates              548           1 309       2 914        5.1       11.8        15.3             0.0              0.0    0.0
Yemen                            1 693          3 370       6 022       20.3       19.8        25.1           98.3              83.2   61.9


LATIN AMERICA AND
                               125 954       196 316      280 321       30.4       35.6        41.8           20.6              11.2    7.4
THE CARIBBEAN


Caribbean                       10 733        14 496       18 380       35.6       35.3        40.8           24.5              15.5   12.2
Anguilla                               2              4          7     50.0        25.0        42.9             0.0              0.0    0.0
Antigua and Barbuda                   26             27       38       34.6        37.0        42.1           22.2              10.0   12.5
Aruba                                 22             32       46       36.4        34.4        43.5           25.0              18.2   10.0
Bahamas                               88         140         186       43.2        45.0        48.4             2.6              1.6    0.0
Barbados                          111            144         154       44.1        47.9        48.1             8.2              4.3    2.7
British Virgin Islands                 4              7       10       25.0        42.9        40.0             0.0              0.0   25.0
Cayman Islands                         6             13       25       33.3        38.5        40.0           50.0              20.0   10.0
Cuba                             3 495          4 853       5 239      31.0        35.4        39.7           10.4               7.4    5.0
Dominica                              26             27       29       38.5        37.0        41.4           20.0              20.0    8.3
Dominican Republic               1 834          2 925       4 491      27.5        27.1        44.8           11.1               8.8    7.3
Grenada                               32             40       45       37.5        35.0        40.0           25.0              14.3   11.1
Guadeloupe                        126            184         213       44.4        47.3        50.7           10.7               2.3    0.0
Haiti                            2 344          2 692       3 940      44.7        33.2        33.1           61.0              53.9   44.0
Jamaica                           951           1 177       1 218      46.6        47.2        44.4           18.1              13.5   10.9
Martinique                        127            170         185       45.7        49.4        51.9             6.9              3.6    1.0
Montserrat                             4              4          3     50.0        25.0        33.3             0.0              0.0    0.0
Netherlands Antilles                  69             82       98       37.7        45.1        49.0             0.0              0.0    0.0
Puerto Rico                       909           1 278       1 512      29.6        37.9        43.1             0.4              0.4    0.2
Saint Kitts and Nevis                 15             17       23       40.0        35.3        39.1           16.7              16.7   11.1
Saint Lucia                           39             61       84       30.8        41.0        41.7           25.0              16.0   11.4
Saint Vincent and
                                      32             43       54       31.3        34.9        40.7           20.0              13.3   13.6
the Grenadines
Trinidad and Tobago               428            519         716       35.5        38.9        44.4             8.6              4.5    2.5
Turks and Caicos Islands               3              6       14       33.3        33.3        42.9             0.0              0.0   16.7
United States Virgin Islands          40             51       50       50.0        49.0        52.0           25.0              16.0   11.5
108                 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A3 (cont.)

                                                                             Economically active population
                                                   Total                                 Female share              Agricultural share of
                                                 (Thousands)                              (% of total)          economically active women
                                                                                                                           (%)

                                     1980           1995         2010            1980        1995        2010   1980      1995      2010


Central America                       29 939        46 462        64 495         30.8        31.7        36.5    18.3       9.9      6.1
Belize                                      39             75        131         17.9        29.3        36.6    14.3       4.5      2.1
Costa Rica                                849         1 411        2 109         27.7        31.4        35.2     4.7       6.1      5.5
El Salvador                             1 592         2 201        2 587         33.9        36.3        41.1     8.5       6.5      5.3
Guatemala                               2 313         2 941        5 367         25.6        23.9        38.3    16.9      14.2     10.0
Honduras                                1 144         1 999        2 782         26.7        32.3        31.5    40.3      22.2     15.8
Mexico                                22 318        35 202        47 529         31.3        32.2        36.6    19.2       9.6      5.5
Nicaragua                               1 016         1 531        2 395         33.2        28.9        32.2    15.7       7.0      3.5
Panama                                    668         1 102        1 595         31.1        32.9        37.7     4.8       2.8      1.5


South America                         85 282       135 358       197 446         29.6        37.0        43.6    20.8      11.1      7.3
Argentina                             10 231        14 320        19 094         28.6        36.7        41.8     3.1       2.6      1.9
Bolivia (Plurinational
                                        1 908         2 837        4 849         32.8        42.0        45.5    53.3      43.3     37.8
State of)
Brazil                                44 710        70 889       101 026         29.4        36.9        44.2    26.3      11.2      6.1
Chile                                   3 756         5 632        7 302         29.0        31.9        37.1     6.4       5.7      5.1
Colombia                                8 764       15 077        23 927         33.0        39.9        46.6    23.0      11.5      7.8
Ecuador                                 2 543         4 260        6 320         24.9        33.6        40.8    21.8      14.7     11.2
Falkland Islands (Malvinas)                  1              1           2          0.0         0.0       50.0
French Guiana                               29             56         91         37.9        39.3        46.2    18.2      13.6      7.1
Guyana                                    252          301           347         25.0        35.5        35.4    11.1       6.5      3.3
Paraguay                                1 267         2 045        3 358         38.4        39.6        45.9     8.6       6.6      4.2
Peru                                    5 597         9 948       15 497         29.6        40.1        44.5    25.1      20.9     17.0
Suriname                                  106          142           195         32.1        33.1        36.9    20.6      14.9     11.1
Uruguay                                 1 242         1 511        1 654         37.8        41.4        44.4     3.8       3.8      3.5
Venezuela (Bolivarian
                                        4 876         8 339       13 784         25.4        31.1        39.9     1.9       1.5      0.8
Republic of)


OCEANIA EXCLUDING
AUSTRALIA AND                           1 903         3 018        4 415         39.3        44.1        45.8    80.5      73.3     67.0
NEW ZEALAND
American Samoa                              11             20         28         27.3        35.0        39.3    66.7      42.9     27.3
Cook Islands                                 6              7           8        33.3        42.9        37.5    50.0     33.3      33.3
Fiji                                      208          291           348         21.2        31.6        32.8    27.3     26.1      23.7
French Polynesia                            56             89        122         33.9        38.2        39.3    47.4     35.3      25.0
Guam                                        43             67         88         37.2        37.3        40.9    25.0     20.0      13.9
Kiribati                                    22             35         48         36.4        40.0        43.8    25.0     21.4      14.3
Marshall Islands                                           23         31                     39.1        45.2             22.2      14.3
Micronesia (Federated
                                                           49         54                     36.7        40.7             22.2      13.6
States of)
Nauru                                        3              5           5        33.3        40.0        40.0     0.0       0.0      0.0
New Caledonia                               49             81        108         36.7        37.0        38.0    55.6     43.3      31.7
Niue                                        1               1           1          0.0         0.0        0.0
Northern Mariana Islands                                   26         43                     38.5        44.2             20.0      15.8
Palau                                                      8          10                     37.5        40.0             33.3      25.0
S t a t is t ic a l a n n ex

                                                                                                                               109
TABLE A3 (cont.)

                                                                  Economically active population
                                          Total                             Female share                     Agricultural share of
                                        (Thousands)                          (% of total)                 economically active women
                                                                                                                             (%)

                            1980           1995        2010         1980        1995        2010           1980          1995       2010


Papua New Guinea              1 278          1 987       3 054       43.3       48.0        49.0           91.5              86.9   79.0
Samoa                              54             61       65        33.3       32.8        33.8           50.0              35.0   27.3
Solomon Islands                    85         144         222        40.0       40.3        38.7           85.3              84.5   80.2
Tokelau                             1              1          0       0.0         0.0
Tonga                              25             33       41        20.0       36.4        43.9           60.0              33.3   27.8
Tuvalu                              3              4          4      33.3       25.0        50.0             0.0              0.0    0.0
Vanuatu                            54             81      129        44.4       46.9        46.5           54.2              42.1   30.0
Wallis and Futuna Islands          4              5           6      25.0       40.0        33.3          100.0              50.0   50.0


COUNTRIES IN DEVELOPED
                            541 644       574 678      625 428       42.3       44.3        46.0           13.4               6.2    3.0
REGIONS


ASIA AND OCEANIA             64 518        77 780       77 707       38.4       40.8        42.7           12.4               5.7    2.5
Australia                     6 750          9 068      11 315       36.7       42.7        45.7             3.9              3.8    3.8
Japan                        56 431        66 883       64 067      38.7        40.5        42.1           13.5               6.0    2.1
New Zealand                   1 337          1 829       2 325      34.0        44.0        46.4             7.0              6.8    5.9


EUROPE                      351 529       341 936      363 492      43.4        44.6        46.6           17.5               8.6    4.1
                                                                                                                                        
Eastern Europe              189 751       149 744      147 999      48.7        47.5        48.6           22.6              11.7    5.5
Belarus                                      5 016       4 880                  48.4        49.1                              9.6    3.4
Bulgaria                      4 718          3 709       3 334      47.9        47.9        46.8           21.9               8.7    2.4
Czech Republic                               5 160       5 242                  44.3        44.5                              7.0    3.2
Czechoslovakia (A)            8 116                                  45.8                                  11.8                         
Hungary                       5 058          4 188       4 318       43.4       43.4        45.6           15.2               8.2    3.7
Poland                       17 568        17 438       17 275       45.5       45.5        45.7           31.9              23.3   13.5
Republic of Moldova                          1 962       1 343                  48.7        52.6                             21.0    8.5
Romania                      10 508        12 122        9 307       46.8       46.3        45.7           45.3              21.3    8.7
Russian Federation                         72 466       76 217                  47.8        49.8                              7.8    4.0
Slovakia                                     2 481       2 757                  44.7        44.9                              7.4    3.4
Ukraine                                    25 202       23 326                  50.0        49.7                             12.6    5.7
USSR   (A)
                            137 459                                  49.7                                  20.3                         
Yugoslav SFR (A)              6 324                                  45.8                                  32.2                         
                                                                                                                                        
Northern Europe              40 445        46 413       51 420       40.6       45.0        46.6             2.7              2.4    1.4
Denmark                       2 666          2 822       2 914       44.9       45.3        47.2             2.8              2.4    1.3
Estonia                                       713         688                   48.2        50.7                              9.0    4.6
Faroe Islands                      22             22       26        40.9       40.9        46.2             0.0              0.0    0.0
Finland                       2 468          2 490       2 724       46.2       47.5        48.3           10.3               5.1    2.7
Iceland                        121            153         195        44.6       47.1        46.2             3.7              4.2    2.2
Ireland                       1 246          1 466       2 328       27.8       37.7        43.6             6.1              2.5    1.1
Latvia                                       1 207       1 219                  48.1        48.5                              9.8    4.7
Lithuania                                    1 790       1 544                  47.7        49.8                              9.8    3.6
110               TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A3 (cont.)

                                                                           Economically active population
                                                 Total                                    Female share              Agricultural share of
                                               (Thousands)                                 (% of total)          economically active women
                                                                                                                            (%)

                                   1980           1995         2010            1980           1995        2010   1980      1995      2010


Norway                                2 006         2 234        2 616         41.4           45.8        47.7     6.0       3.6      2.8
Sweden                                4 437         4 555        5 029         45.1           47.4        47.6     3.7       2.4      1.7
United Kingdom                      27 479        28 961        32 137         39.4           44.3        46.1     1.4       1.0      0.8
                                                                                                                                         
Southern Europe                     46 186        61 050        71 677         32.8           39.0        43.0    21.8      12.8      6.5
Albania                               1 296         1 308        1 450         43.1           40.8        42.8    62.4      55.8     42.3
Andorra                                   16             28          41        31.3           35.7        41.5    20.0      10.0      5.9
Bosnia and Herzegovina                              1 636        1 876                        46.1        46.6              10.6      3.0
Croatia                                             2 104        1 938                        43.4        45.1              10.3      2.9
Gibraltar                                 12             12         15         33.3           33.3        40.0    25.0      25.0      0.0
Greece                                3 881         4 537        5 218         33.8           36.7        41.2    42.3      24.9     15.3
Holy See                                   0              0           0                                                                  
Italy                               22 134        23 058        25 775         33.7           36.8        42.1    14.5       7.2      3.5
Malta                                   120          140           172         23.3           26.4        34.3     3.6       0.0      0.0
Montenegro                                                         305                                    44.9                       10.9
Portugal                              4 467         4 880        5 696         39.6           44.6        46.9    33.6      18.7     12.3
San Marino                                9              11         15         33.3           36.4        40.0    33.3       0.0      0.0
Serbia (A)                                                       4 806                                    44.7                       10.9
Serbia and Montenegro (A)                           4 893                                     45.0                          25.4         
Slovenia                                             949         1 025                        46.0        46.1               3.7      0.6
Spain                               14 251        16 688        22 439         28.3           37.7        42.8    18.2       8.2      3.9
The former Yugoslav
                                                     806           906                        37.2        39.4              16.7      6.2
Republic of Macedonia
                                                                                                                                         
Western Europe                      75 147        84 729        92 396         38.2           43.1        46.1     7.3       3.3      1.5
Austria                               3 244         3 845        4 295         38.4           43.0        46.1    12.2       7.0      3.3
Belgium                                                          4 713                                    45.4                        0.9
Belgium-Luxembourg (A)                4 040         4 337                      35.8           41.1                 2.1       1.5         
France                              24 001        25 382        28 232         40.0           44.9        46.9     7.4       3.4      1.4
Germany                             35 415        39 754        41 914         38.4           42.5        45.6     8.1       3.0      1.3
Liechtenstein                             11             15          18        36.4           40.0        44.4     0.0       0.0      0.0
Luxembourg                                                         228                                    44.7                        1.0
Monaco                                    11             14          16        36.4           42.9        43.8     0.0       0.0      0.0
Netherlands                           5 388         7 454        8 713         31.2           41.3        45.9     3.0       2.9      2.0
Switzerland                           3 037         3 928        4 267         36.5           43.3        46.6     4.4       3.9      3.0
                                                                                                                                         
NORTHERN AMERICA                   125 597       154 962       184 229         41.2           45.4        46.2     2.1       1.3      1.0
Bermuda                                   28             32         34         39.3           43.8        44.1     0.0       0.0      0.0
Canada                              12 102        15 023        19 320         39.7           45.0        47.5     6.1       2.3      1.9
Greenland                                 25             29         30         40.0           44.8        46.7     0.0       0.0      0.0
Saint Pierre and Miquelon                 3               3           3        33.3           33.3        33.3     0.0       0.0      0.0
United States of America           113 439       139 875       164 842         41.4           45.4        46.0     1.6       1.2      0.9
S t a t is t ic a l a n n ex

                                                                                                                                         111
TABLE A4
Economically active population, agricultural share of economically active population and female share
of economically active in agriculture in 1980, 1995 and 2010

                                                                      Economically active population
                                             Total                          Agricultural share               Female share of economically
                                           (Thousands)                          (% of total)                     active in agriculture
                                                                                                                                  (%)

                               1980           1995          2010        1980       1995        2010             1980          1995        2010


WORLD                         1 894 978    2 575 394      3 282 308      50.4      46.1          39.9           40.4              41.9    42.7


COUNTRIES IN DEVELOPING
                              1 353 280    2 000 716      2 656 880      65.3      57.2          48.2           40.1              42.1    42.9
REGIONS


AFRICA                         172 652       268 197       407 905       68.4      60.3          53.1           44.3              46.4    48.5


Sub-Saharan Africa            147 699       227 175       346 919       71.9       65.4        58.4             46.0          47.1        48.7


Eastern Africa                  61 341        97 031       152 689       84.7      80.6          74.5           49.6              50.6    51.3
Burundi                          1 977          2 978        4 260       93.2      91.4          89.2           55.9              55.9    56.0
Comoros                            151           250           387       80.8      75.6          69.5           50.0              50.3    52.0
Djibouti                           133           249           381       84.2      79.9          74.0           46.4              47.2    46.5
Eritrea                                         1 200        2 086                 78.7          73.7                             44.6    43.6
Ethiopia                                      24 306        41 929                 84.4          77.3                             43.0    45.5
Ethiopia PDR (A)                14 833                                   88.9                                   41.0
Kenya                            6 718        12 139        18 887       82.2      77.6          70.6           49.0              49.5    48.6
Madagascar                       3 880          5 966       10 060       82.3      76.9          70.1           54.7              53.9    53.5
Malawi                           2 876          4 302        6 542       87.4      85.1          79.1           56.7              56.1    59.2
Mauritius                          370           485           589       27.3      14.0           8.1           29.7              26.5    25.0
Mozambique                       5 951          7 547       10 778       84.8      83.6          80.5           58.6              63.4    65.2
Réunion                            170           270           362       28.2        4.8          1.4           10.4               7.7    20.0
Rwanda                           2 328          2 327        4 722       93.1      91.5          89.4           55.3              56.1    57.0
Seychelles                            28             33         40       85.7      81.8          72.5           50.0              48.1    51.7
Somalia                          2 437          2 565        3 731       77.2      72.3          65.6           44.4              45.3    45.9
Uganda                           5 679          9 225       14 896      87.1       82.4          74.8           49.5              49.9    49.5
United Republic of Tanzania      9 084        14 855        22 339      85.8       82.6          75.9           53.7              54.1    55.0
Zambia                           1 985          3 481        5 146      74.7       71.8          63.3           41.2              47.6    46.5
Zimbabwe                         2 741          4 853        5 554      73.0       66.0          56.5           54.3              55.3    53.3


Middle Africa                   21 068        33 670        50 767      73.9       67.0          57.7           49.4              50.1    50.8
Angola                           3 421          5 397        8 447      76.1       73.0          69.3           52.4              52.6    55.0
Cameroon                         3 402          5 086        7 622      74.5       65.3          47.7           50.1              47.4    47.3
Central African Republic         1 018          1 476        2 030      84.5       76.6          63.3           49.8              50.2    49.9
Chad                             1 547          2 790        4 623      85.6       79.7          65.7           28.9              50.8    56.9
Congo                              700          1 099        1 524      57.3       44.4          32.0           56.6              60.0    56.5
Democratic Republic of
                                10 558        17 137        25 488      71.5       64.8          57.3           51.3              49.5    48.8
the Congo
Equatorial Guinea                     87         174           268      77.0       71.8          64.9           40.3              40.8    43.7
Gabon                              305           472           708      65.6       44.5          25.7           50.5              49.5    45.6
Sao Tome and Principe                 30             39         57      70.0       64.1          56.1           38.1              44.0    50.0
112               TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A4 (cont.)

                                                                           Economically active population
                                                 Total                                Agricultural share          Female share of economically
                                               (Thousands)                                (% of total)                active in agriculture
                                                                                                                              (%)

                                   1980           1995         2010            1980          1995        2010      1980       1995      2010


Northern Africa                     31 554        50 078        74 694         53.1          37.8          28.3     30.1      37.0      42.8
Algeria                               4 555         9 018       14 950         35.9          25.9          21.2     41.5      50.4      52.7
Egypt                               11 780        18 531        27 492         53.8          35.0          25.1     25.9      34.9      40.3
Libyan Arab Jamahiriya                  838         1 517        2 425         22.4            7.6          3.0     37.2      50.0      69.9
Morocco                               5 848         9 015       11 963         53.0          37.1          25.5     29.0      38.9      47.7
Sudan                                 6 601         9 056       13 708         72.1          65.1          51.5     32.5      32.9      39.5
Tunisia                               1 865         2 829        3 886         37.0          25.4          20.5     27.1      34.4      32.8
Western Sahara                            67         112           270         56.7          41.1          30.4     42.1      47.8      53.7


Southern Africa                     10 753        16 325        21 371         21.8          15.3          10.6     43.8      40.9      42.5
Botswana                                332          506           741         61.4          44.9          42.2     46.6      52.4      56.9
Lesotho                                 538          720           895         45.2          43.2          39.3     72.0      68.2      67.3
Namibia                                 309          507           769         57.3          45.4          33.6     52.5      47.8      44.6
South Africa                          9 350       14 220        18 481         17.2          11.1           6.5     37.1      31.1      29.6
Swaziland                               224          372           485         52.7          39.0          28.9     58.5      60.7      54.3


Western Africa                      47 936        71 093       108 384         65.7          55.6          46.4     40.7      40.9      43.3
Benin                                 1 168         2 240        3 778         67.0          58.7          44.3     34.5      41.1      39.6
Burkina Faso                          2 989         4 421        7 425         92.2          92.3          92.1     46.7      48.1      47.7
Cape Verde                                90         131           195         36.7          26.7          16.9     42.4      40.0      42.4
Côte d’Ivoire                         3 096         5 407        8 106         64.6          54.1          37.9     35.3      35.6      36.2
Gambia                                  273          483           806         84.6          80.5          75.9     50.6      51.2      53.3
Ghana                                 4 473         7 247       11 116         61.6          58.2          54.5     45.6      45.1      44.3
Guinea                                2 210         3 535        4 968         90.9          85.6          79.8     50.4      49.5      49.7
Guinea-Bissau                           331          451           613         87.3          84.0          79.3     43.9      45.9      45.5
Liberia                                 711          719         1 509         76.8          70.1          62.1     46.7      45.6      44.5
Mali                                  1 963         2 508        3 517         88.3          83.0          74.9     36.6      35.9      37.7
Mauritania                              603          913         1 441         71.1          53.9          50.2     47.6      49.2      53.9
Niger                                 1 965         3 045        5 228         90.2          87.2          82.9     36.5      36.1      36.6
Nigeria                             23 353        33 165        49 144         53.9          38.0          24.9     36.6      34.8      39.7
Saint Helena                              2              2            2        50.0          50.0          50.0    100.0       0.0       0.0
Senegal                               2 382         3 591        5 626         80.4          75.0          70.2     44.9      45.5      47.4
Sierra Leone                          1 265         1 546        2 197         73.0          67.9          60.1     59.0      58.5      61.7
Togo                                  1 062         1 689        2 713         68.7          62.7          53.4     38.8      38.4      41.3


ASIA EXCLUDING JAPAN             1 052 771     1 533 185     1 964 239         68.6          61.1          52.0     40.7      42.5      42.6


Central Asia                                      21 059        29 095                       27.6          20.5               42.4      41.0
Kazakhstan                                         7 773         8 427                       19.7          13.8               30.4      24.4
Kyrgyzstan                                         1 885         2 547                       28.9          20.8               37.7      29.8
Tajikistan                                         1 678         2 896                       37.4          27.4               52.2      53.0
Turkmenistan                                       1 635         2 437                       35.4          29.7               51.6      53.0
Uzbekistan                                         8 088        12 788                       31.2          21.4               46.2      43.5
 
S t a t is t ic a l a n n ex

                                                                                                                                        113
TABLE A4 (cont.)

                                                                      Economically active population
                                            Total                           Agricultural share               Female share of economically
                                          (Thousands)                           (% of total)                     active in agriculture
                                                                                                                                  (%)

                             1980            1995         2010          1980       1995        2010             1980          1995       2010


Eastern Asia excluding
                             526 764        737 152       855 786        72.4      67.2          58.6           45.8              47.6   47.9
Japan
China (A)                    504 496        704 769       817 033        73.9      69.4          60.8           45.8              47.7   47.9
China, Hong Kong SAR           2 415           3 086        3 759         1.3        0.6          0.2           31.3              31.6   25.0
China, Macao SAR                     ..              ..          ..        ..          ..          ..               ..              ..     ..
China, mainland                      ..              ..          ..        ..          ..          ..               ..              ..     ..
Democratic People’s
                               7 103         10 400        12 979        44.2      33.8          23.3           46.7              45.0   46.0
Republic of Korea
Mongolia                        574             862         1 204        39.7      28.0          17.9           42.1              44.0   47.9
Republic of Korea             14 591         21 121        24 570        36.9      13.5           5.2           47.1              43.8   43.8


Southeastern Asia            147 907        221 405       299 123        63.2      56.0          46.8           41.9              42.7   42.5
Brunei Darussalam                   71          131          195          5.6        1.5          0.5           25.0               0.0    0.0
Cambodia                       3 209           4 930        8 029        75.5      71.9          65.9           57.3              54.9   51.2
Indonesia                     55 181         84 276       115 905       57.8       51.7          41.4           33.7              39.0   39.3
Lao People’s Democratic
                               1 463           2 172        3 281       79.8       77.5          74.9           51.3              51.8   52.3
Republic
Malaysia                       4 984           8 167       12 445       40.9       22.8          12.7           41.7              28.6   21.0
Myanmar                       15 972         22 769        29 464       75.9       71.9          67.1           47.5              47.6   48.3
Philippines                   17 861         28 019        39 967       51.5       42.6          33.7           27.6              24.5   24.0
Singapore                      1 117           1 740        2 637         1.5        0.2          0.1           29.4              25.0    0.0
Thailand                      23 709         33 490        39 198       70.9       60.3          48.5           49.1              45.9   45.0
Timor-Leste                     242             332          461        83.9       81.9          79.6           44.8              42.6   45.0
Viet Nam                      24 098         35 379        47 541       73.2       69.4          63.2           50.7              51.0   49.1


Southern Asia                348 669        496 504       699 660       67.2       59.3          51.1           32.3              33.6   34.9
Afghanistan                    4 548           5 620        9 384       70.4       65.8          59.7           29.4              28.5   32.1
Bangladesh                    38 345         56 409        78 232       71.9       59.9          45.4           42.4              44.5   51.0
Bhutan                          146             150          326        93.8       92.7          92.9           26.3              19.4   34.7
India                        259 177        364 665       491 326       68.2       61.4          54.4           32.4              32.8   32.4
Iran (Islamic Republic of)    11 064         18 288        30 746       39.0       29.4          21.6           25.2              33.9   46.4
Maldives                            46              70       150        52.2       28.6          14.7           16.7              20.0   40.9
Nepal                          5 837           8 061       12 936       93.4       93.4          92.9           35.4              42.2   48.1
Pakistan                      23 563         35 980        67 292       58.5       45.7          39.0           12.2              18.4   29.6
Sri Lanka                      5 943           7 261        9 268       52.2       47.0          42.5           34.8              34.2   37.4


Western Asia                  29 431         57 065        80 575       44.0       30.4          19.2           35.0              43.0   47.9
Armenia                                        1 375        1 575                  14.9           9.4                             25.9   16.2
Azerbaijan                                     3 229        4 633                  29.0          22.8                             53.8   53.9
Bahrain                         136             263          384          3.7        1.5          0.5             0.0              0.0    0.0
Cyprus                          282             343          446        25.5       10.8           5.4           45.8              40.5   41.7
Georgia                                       2 508         2 278                  22.8          15.1                             42.3   36.2
Iraq                           3 097          5 018         7 918       26.6       11.9           5.5           29.7              38.2   50.3
Israel                         1 271          2 039         2 935         6.1        3.2          1.7           22.1              22.7   21.6
114                 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A4 (cont.)

                                                                             Economically active population
                                                   Total                                Agricultural share          Female share of economically
                                                 (Thousands)                                (% of total)                active in agriculture
                                                                                                                                (%)

                                     1980           1995         2010            1980          1995        2010      1980       1995      2010


Jordan                                    444         1 160        1 882         16.7          11.3           6.3     41.9      44.3      62.2
Kuwait                                    457          823         1 541           2.0           1.2          1.0      0.0       0.0       0.0
Lebanon                                   857         1 190        1 563         14.0            5.1          1.8     28.3      32.8      32.1
Occupied Palestinian
                                          465          866         1 508         23.2          14.8           8.0     64.8      64.1      72.5
Territory (A)
Oman                                      341          778         1 123         47.2          40.6          28.5      9.3       5.4       7.5
Qatar                                     106          284           976           2.8           1.8          0.7      0.0       0.0       0.0
Saudi Arabia                            2 415         5 752        9 570         43.0          14.1           5.1      5.8       6.0       5.7
Syrian Arab Republic                    2 020         4 240        7 365         33.6          28.5          20.0     31.7      50.7      60.7
Turkey                                15 299        22 518        25 942         56.2          46.2          32.3     40.4      48.2      52.3
United Arab Emirates                      548         1 309        2 914           4.6           6.3          3.1      0.0       0.0       0.0
Yemen                                   1 693         3 370        6 022         67.9          52.4          38.8     29.3      31.4      40.1


LATIN AMERICA AND
                                     125 954       196 316       280 321         33.6          22.0          14.8     18.6      18.1      20.9
THE CARIBBEAN


Caribbean                             10 733        14 496        18 380         33.6          25.3          20.4     26.0      21.6      24.5
Anguilla                                     2              4           7        50.0          25.0          14.3      0.0       0.0       0.0
Antigua and Barbuda                         26             27         38         34.6          25.9          21.1     22.2      14.3      25.0
Aruba                                       22             32         46         31.8          25.0          19.6     28.6      25.0      22.2
Bahamas                                     88         140           186           5.7           4.3          2.7     20.0      16.7       0.0
Barbados                                  111          144           154           9.9           5.6          2.6     36.4      37.5      50.0
British Virgin Islands                       4              7         10         25.0          28.6          20.0      0.0       0.0      50.0
Cayman Islands                               6             13         25         33.3          23.1          20.0     50.0      33.3      20.0
Cuba                                    3 495         4 853        5 239         23.7          16.4          11.1     13.5      16.1      17.9
Dominica                                    26             27         29         34.6          25.9          20.7     22.2      28.6      16.7
Dominican Republic                      1 834         2 925        4 491         31.7          20.8          10.5      9.6      11.5      31.2
Grenada                                     32             40         45         34.4          25.0          20.0     27.3      20.0      22.2
Guadeloupe                                126          184           213         18.3            4.3          1.4     26.1      25.0       0.0
Haiti                                   2 344         2 692        3 940         70.9          67.1          58.8     38.4      26.7      24.8
Jamaica                                   951         1 177        1 218         31.1          22.5          17.5     27.0      28.3      27.7
Martinique                                127          170           185         12.6            5.3          2.2     25.0      33.3      25.0
Montserrat                                   4              4           3        25.0          25.0          33.3      0.0       0.0       0.0
Netherlands Antilles                        69             82         98           0.0           0.0          0.0       ..        ..         ..
Puerto Rico                               909         1 278        1 512           5.9           3.1          1.1      1.9       5.1       5.9
Saint Kitts and Nevis                       15             17         23         33.3          23.5          21.7     20.0      25.0      20.0
Saint Lucia                                 39             61         84         33.3          24.6          20.2     23.1      26.7      23.5
Saint Vincent and
                                            32             43         54         34.4          25.6          20.4     18.2      18.2      27.3
the Grenadines
Trinidad and Tobago                       428          519           716         10.7            9.6          6.6     28.3      18.0      17.0
Turks and Caicos Islands                     3              6         14         33.3          33.3          21.4      0.0       0.0      33.3
United States Virgin Islands                40             51         50         32.5          23.5          18.0     38.5      33.3      33.3
S t a t is t ic a l a n n ex

                                                                                                                                           115
TABLE A4 (cont.)

                                                                         Economically active population
                                                 Total                         Agricultural share               Female share of economically
                                               (Thousands)                         (% of total)                     active in agriculture
                                                                                                                                     (%)

                                   1980           1995        2010         1980       1995        2010             1980          1995       2010


Central America                    29 939         46 462       64 495       37.5      26.8          18.6           15.0              11.7   11.9
Belize                                    39             75      131        41.0      29.3          23.7             6.3              4.5    3.2
Costa Rica                            849           1 411       2 109       32.4      22.5          15.2             4.0              8.5   12.8
El Salvador                         1 592           2 201       2 587       39.8      31.6          22.7             7.3              7.5    9.6
Guatemala                           2 313           2 941       5 367       52.3      50.4          38.4             8.3              6.8   10.0
Honduras                            1 144           1 999       2 782       56.8      35.9          24.0           18.9              19.9   20.7
Mexico                             22 318         35 202       47 529       35.3      24.4          16.2           17.0              12.7   12.3
Nicaragua                           1 016           1 531       2 395       37.7      25.4          14.7           13.8               8.0    7.6
Panama                                668           1 102       1 595       28.6      23.4          15.5             5.2              3.9    3.6


South America                      85 282        135 358      197 446       32.3      20.0          13.0           19.1              20.5   24.6
Argentina                          10 231         14 320       19 094       12.8      10.2           7.4             6.9              9.3   10.7
Bolivia (Plurinational State of)    1 908           2 837       4 849       52.8      45.3          41.1           33.0              40.1   41.8
Brazil                             44 710         70 889      101 026      36.5       19.5          11.0           21.2              21.2   24.5
Chile                               3 756           5 632       7 302      20.4       17.2          13.2             9.2             10.6   14.2
Colombia                            8 764         15 077       23 927      38.9       22.9          14.8           19.5              19.9   24.8
Ecuador                             2 543           4 260       6 320      38.7       28.0          18.5           14.0              17.6   24.8
Falkland Islands (Malvinas)                1              1          2       0.0        0.0          0.0
French Guiana                             29             56       91       31.0       19.6          13.2           22.2              27.3   25.0
Guyana                                252            301         347       26.6       19.3          14.7           10.4              12.1    7.8
Paraguay                            1 267           2 045       3 358      39.0       32.1          24.8             8.5              8.1    7.7
Peru                                5 597           9 948      15 497      39.1       31.0          24.2           19.0              27.0   31.3
Suriname                              106            142         195       23.6       19.7          16.9           28.0              25.0   24.2
Uruguay                             1 242           1 511       1 654      15.4       13.3          11.2             9.4             11.9   14.0
Venezuela (Bolivarian
                                    4 876           8 339      13 784      14.8       10.1           5.3             3.3              4.6    6.4
Republic of)


OCEANIA EXCLUDING
AUSTRALIA AND                       1 903           3 018       4 415      72.1       65.8          59.0           43.8              49.1   52.0
NEW ZEALAND
American Samoa                            11             20       28       45.5       40.0          28.6           40.0              37.5   37.5
Cook Islands                               6              7          8     50.0       42.9          25.0           33.3              33.3   50.0
Fiji                                  208            291         348       46.2       41.2          35.9           12.5              20.0   21.6
French Polynesia                          56             89      122       48.2       38.2          27.0           33.3              35.3   36.4
Guam                                      43             67       88       37.2       29.9          22.7           25.0              25.0   25.0
Kiribati                                  22             35       48       36.4       28.6          22.9           25.0              30.0   27.3
Marshall Islands                                         23       31                  30.4          22.6                             28.6   28.6
Micronesia (Federated
                                                         49       54                  28.6          22.2                             28.6   25.0
States of)
Nauru                                      3              5          5     33.3       20.0          20.0             0.0              0.0    0.0
New Caledonia                             49             81      108       49.0       39.5          30.6           41.7              40.6   39.4
Niue                                      1               1          1    100.0         0.0          0.0             0.0
Northern Mariana Islands                                 26       43                  30.8          23.3                             25.0   30.0
Palau                                                    8        10                  25.0          20.0                             50.0   50.0
116                      TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A4 (cont.)

                                                                                  Economically active population
                                                        Total                                Agricultural share          Female share of economically
                                                      (Thousands)                                (% of total)                active in agriculture
                                                                                                                                     (%)

                                          1980           1995         2010            1980          1995        2010      1980       1995      2010


Papua New Guinea                             1 278         1 987        3 054         82.7          77.9          69.4     47.9      53.5      55.8
Samoa                                            54             61          65        48.1          39.3          27.7     34.6      29.2      33.3
Solomon Islands                                  85         144           222         77.6          73.6          67.6     43.9      46.2      46.0
Tokelau                                           1              1           0          0.0           0.0
Tonga                                            25             33          41        48.0          39.4          26.8     25.0      30.8      45.5
Tuvalu                                            3              4           4        33.3          25.0          25.0      0.0       0.0       0.0
Vanuatu                                          54             81        129         50.0          40.7          30.2     48.1      48.5      46.2
Wallis and Futuna Islands                        4              5            6        50.0          40.0          33.3     50.0      50.0      50.0


COUNTRIES IN DEVELOPED
                                          541 644       574 678       625 428         13.1            7.5          4.2     43.4      36.9      32.7
REGIONS


ASIA AND OCEANIA                           64 518        77 780        77 707         10.5            5.5          2.6     45.4      42.7      40.8
Australia                                    6 750         9 068       11 315           6.5           5.0          3.9     22.1      32.8      44.9
Japan                                      56 431        66 883        64 067         11.0            5.4          2.2     47.6      44.5      40.3
New Zealand                                  1 337         1 829        2 325         11.2            9.6          7.9     21.3      31.3      34.8


EUROPE                                    351 529       341 936       363 492         16.9          10.2           5.9     44.9      37.5      32.4


Eastern Europe                            189 751       149 744       147 999         23.0          15.1           9.4     47.8      36.9      28.5
Belarus                                                    5 016        4 880                       16.2           8.9               28.8      18.7
Bulgaria                                     4 718         3 709        3 334         20.3            9.8          3.7     51.9      42.7      30.6
Czech Republic                                             5 160        5 242                         9.7          6.2               32.1      23.1
Czechoslovakia     (A)
                                             8 116                                    13.3                                 40.7
Hungary                                      5 058         4 188        4 318         18.4          12.8           7.4     35.9      27.7      22.7
Poland                                     17 568        17 438        17 275         29.8          24.5          17.0     48.7      43.4      36.2
Republic of Moldova                                        1 962        1 343                       27.5          14.9               37.2      30.0
Romania                                    10 508        12 122         9 307         35.0          19.2           9.2     60.6      51.4      43.2
Russian Federation                                       72 466        76 217                       12.1           8.0               31.1      24.7
Slovakia                                                   2 481        2 757                       10.6           7.1               31.2      21.5
Ukraine                                                  25 202        23 326                       16.9          10.3               37.4      27.4
USSR (A)                                  137 459                                     21.8                                 46.2
Yugoslav SFR (A)                             6 324                                    27.5                                 53.5


Northern Europe                            40 445        46 413        51 420           4.6           4.0          2.5     23.7      26.3      25.4
Denmark                                      2 666         2 822        2 914           6.9           4.6          2.5     18.5      23.7      24.3
Estonia                                                     713           688                       12.9           8.9               33.7      26.2
Faroe Islands                                    22             22          26          4.5           4.5          3.8      0.0       0.0       0.0
Finland                                      2 468         2 490        2 724         12.1            6.8          3.6     39.3      35.3      36.1
Iceland                                        121          153           195           9.9           9.2          6.2     16.7      21.4      16.7
Ireland                                      1 246         1 466        2 328         18.6          11.5           6.6      9.1       8.3       7.2
Latvia                                                     1 207        1 219                       13.8           9.2               34.1      25.0
Lithuania                                                  1 790        1 544                       15.1           8.0               31.0      22.6
S t a t is t ic a l a n n ex

                                                                                                                                    117
TABLE A4 (cont.)

                                                                  Economically active population
                                          Total                         Agricultural share               Female share of economically
                                        (Thousands)                         (% of total)                     active in agriculture
                                                                                                                              (%)

                            1980           1995        2010         1980       1995        2010             1980          1995       2010


Norway                        2 006          2 234       2 616        8.2        5.3          3.4           30.3              31.1   39.8
Sweden                        4 437          4 555       5 029        6.1        3.7          2.3           27.3              30.0   36.0
United Kingdom               27 479        28 961       32 137        2.6        2.0          1.5           20.6              21.7   24.9


Southern Europe              46 186        61 050       71 677       18.6      11.8           6.2           38.5              42.4   45.0
Albania                       1 296          1 308       1 450       57.6      51.5          41.8           46.6              44.3   43.2
Andorra                            16             28       41        18.8      10.7           4.9           33.3              33.3   50.0
Bosnia and Herzegovina                       1 636       1 876                   8.1          2.3                             60.6   59.1
Croatia                                      2 104       1 938                 11.7           4.4                             38.1   29.4
Gibraltar                          12             12       15        16.7        8.3          6.7           50.0         100.0        0.0
Greece                        3 881          4 537       5 218       32.1      19.7          12.0           44.6              46.5   52.6
Holy See                            -              -          -
Italy                        22 134        23 058       25 775       12.6        6.8          3.3           38.5              38.9   45.2
Malta                          120            140         172         8.3        2.1          1.2           10.0               0.0    0.0
Montenegro                                                305                                12.8                                    38.5
Portugal                      4 467          4 880       5 696       26.1      15.2           9.1           50.9              54.9   63.7
San Marino                         9              11       15       22.2         9.1          6.7           50.0               0.0    0.0
Serbia (A)                                               4 806                               12.8                                    38.1
Serbia and Montenegro (A)                    4 893                             24.5                                           46.5
Slovenia                                      949        1 025                   3.4          0.7                             50.0   42.9
Spain                        14 251        16 688       22 439       18.4        9.3          4.4           28.0              33.2   37.7
The former Yugoslav
                                              806         906                  16.7           7.5                             37.0   32.4
Republic of Macedonia


Western Europe               75 147        84 729       92 396        7.1        3.7          1.9           38.9              38.0   36.8
Austria                       3 244          3 845       4 295        9.8        6.3          3.4           47.6              47.5   45.8
Belgium                                                  4 713                                1.3                                    32.2
Belgium-Luxembourg (A)        4 040          4 337                    3.0        2.2                        24.6              28.1
France                       24 001        25 382       28 232        8.3        4.3          2.0           35.7              35.6   33.6
Germany                      35 415        39 754       41 914        6.9        3.2          1.6           44.9              40.9   36.8
Liechtenstein                      11             15       18         9.1        6.7          0.0             0.0              0.0
Luxembourg                                                228                                 1.3                                    33.3
Monaco                             11             14       16         9.1        7.1          0.0             0.0              0.0
Netherlands                   5 388          7 454       8 713        5.6        3.9          2.5           16.7              30.9   36.4
Switzerland                   3 037          3 928       4 267        6.2        4.8          3.2           26.1              35.8   43.4


NORTHERN AMERICA            125 597       154 962      184 229        3.8        2.5          1.6           22.5              24.4   28.9
Bermuda                            28             32       34         3.6        3.1          2.9             0.0              0.0    0.0
Canada                       12 102        15 023       19 320        6.7        2.8          1.7           36.2              37.1   52.6
Greenland                          25             29       30         4.0        3.4          0.0             0.0              0.0     ..
Saint Pierre and Miquelon          3              3           3       0.0        0.0          0.0               ..              ..     ..
United States of America    113 439       139 875      164 842        3.5        2.4          1.6           19.7              22.8   25.9
118                 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A5
Share of households in rural areas that are female-headed, most recent and earliest observations,
and total agricultural holders and female share of agricultural holders, most recent observations

                                                               Share of rural households                     Agricultural holders
                                                                that are female headed
                                                                             (%)                       (Thousands)          (% of total)

                                                           Most recent                    Earliest        Total            Female share
                                                           observation                  observation


WORLD


COUNTRIES IN DEVELOPING REGIONS


AFRICA                                                           25.5


Sub-Saharan Africa                                               26.2


Eastern Africa                                                   29.9
Burundi                                                             ..                         ..             ..                     ..
Comoros                                                          31.9                          ..        52 464                  32.6
Djibouti                                                            ..                         ..             ..                     ..
Eritrea                                                          43.2                       25.9              ..                     ..
Ethiopia                                                         20.1                       21.3      11 507 442                 18.7
Ethiopia PDR                                                        ..                         ..             ..                     ..
Kenya                                                            33.8                       35.3              ..                     ..
Madagascar                                                       20.6                       20.8       2 428 492                 15.3
Malawi                                                           26.3                       26.1       1 561 416                 32.1
Mauritius                                                           ..                         ..             ..                     ..
Mozambique                                                       26.3                       28.2       3 064 195                 23.1
Réunion                                                             ..                         ..             ..                     ..
Rwanda                                                           34.0                       20.8              ..                     ..
Seychelles                                                          ..                         ..             ..                     ..
Somalia                                                             ..                         ..             ..                     ..
Uganda                                                           29.3                       23.8       1 704 721                 16.3
United Republic of Tanzania (B)                                  25.0                       17.2       4 901 837                 19.7
Zambia                                                           25.4                       18.7       1 305 783                 19.2
Zimbabwe                                                         42.6                       39.4              ..                     ..


Middle Africa                                                    21.6
Angola                                                           21.8                          ..             ..                     ..
Cameroon                                                         22.9                       16.8              ..                     ..
Central African Republic                                         18.8                          ..             ..                     ..
Chad                                                             19.1                       21.5              ..                     ..
Congo                                                            23.4                          ..             ..                     ..
Democratic Republic of the Congo                                 20.0                          ..      4 479 600                    8.9
Equatorial Guinea                                                   ..                         ..             ..                     ..
Gabon                                                            25.4                          ..             ..                     ..
Sao Tome and Principe                                               ..                         ..             ..                     ..
S t a t is t ic a l a n n ex

                                                                                           119
TABLE A5 (cont.)

                            Share of rural households                Agricultural holders
                             that are female headed
                                       (%)                    (Thousands)                 (% of total)

                         Most recent           Earliest           Total                   Female share
                         observation         observation


Northern Africa
Algeria                         ..                  ..        1 023 799                         4.1
Egypt                        12.0                10.9         4 537 319                         5.2
Libyan Arab Jamahiriya          ..                  ..                 ..                         ..
Morocco                      12.0                13.3         1 492 844                         4.4
Sudan                           ..                  ..                 ..                         ..
Tunisia                         ..                  ..                 ..                         ..
Western Sahara                  ..                  ..                 ..                         ..


Southern Africa              46.5
Botswana                        ..                  ..           51 264                        33.9
Lesotho                      36.3                   ..          337 795                        30.8
Namibia                      47.4                30.6                  ..                         ..
South Africa                 50.0                   ..                 ..                         ..
Swaziland                    52.1                   ..                 ..                         ..


Western Africa               19.2                 14.6
Benin                        21.1                 14.2                 ..                         ..
Burkina Faso                   7.5                 5.0          886 638                         8.4
Cape Verde                      ..                  ..           44 450                        50.5
Côte d’Ivoire                13.3                 13.2        1 117 667                        10.1
Gambia                          ..                  ..           69 140                         8.3
Ghana                        30.8                 34.6                 ..                         ..
Guinea                       15.8                 10.8          840 454                         5.7
Guinea-Bissau                   ..                  ..                 ..                         ..
Liberia                      26.6                 28.8                 ..                         ..
Mali                         11.5                  7.0          805 194                         3.1
Mauritania                   31.7                   ..                 ..                         ..
Niger                        18.8                  8.5                 ..                         ..
Nigeria                      18.6                 12.9                 ..                         ..
Saint Helena                    ..                  ..                 ..                         ..
Senegal                      10.7                 10.5          437 036                         9.1
Sierra Leone                 20.7                   ..                 ..                         ..
Togo                         22.1                   ..                 ..                         ..


ASIA EXCLUDING JAPAN


Central Asia                 17.6
Kazakhstan                   22.0                 23.4                 ..                         ..
Kyrgyzstan (2)               18.0                   ..          246 901                        12.3
Tajikistan                      ..                  ..                 ..                         ..
120                 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A5 (cont.)

                                                               Share of rural households                      Agricultural holders
                                                                that are female headed
                                                                             (%)                        (Thousands)          (% of total)

                                                           Most recent                    Earliest         Total            Female share
                                                           observation                  observation


Turkmenistan                                                     18.6                          ..              ..                     ..
Uzbekistan                                                       11.6                          ..              ..                     ..


Eastern Asia excluding Japan                                        ..                         ..              ..                     ..
China                                                               ..                         ..              ..                     ..
China, Hong Kong SAR                                                ..                         ..              ..                     ..
China, Macao SAR                                                    ..                         ..              ..                     ..
China, mainland                                                     ..                         ..              ..                     ..
Democratic People’s Republic of Korea                               ..                         ..              ..                     ..
Mongolia                                                            ..                         ..              ..                     ..
Republic of Korea                                                   ..                         ..              ..                     ..


Southeastern Asia                                                                                      35 581 830                 13.3
Brunei Darussalam                                                   ..                         ..              ..                     ..
Cambodia                                                         23.0                       25.0               ..                     ..
Indonesia   (B)
                                                                 12.3                       12.8       20 331 746                    8.8
Lao People’s Democratic Republic                                    ..                         ..        667 900                     9.1
Malaysia (B)                                                        ..                         ..        500 307                  13.1
Myanmar                                                             ..                         ..       3 464 769                 15.0
Philippines                                                      14.4                       12.1        4 768 317                 10.8
Singapore                                                           ..                         ..              ..                     ..
Thailand                                                            ..                         ..       5 787 774                 27.4
Timor-Leste                                                         ..                         ..              ..                     ..
Viet Nam (3) (B)                                                 22.4                       20.7          61 017                     8.8
                                                                                                                                        
Southern Asia
Afghanistan                                                         ..                         ..              ..                     ..
Bangladesh (4)(5)                                                13.2                        8.7               ..                     ..
Bhutan                                                              ..                         ..              ..                     ..
India (6)                                                        14.9                        9.1      119 621 000                 10.9
Iran (Islamic Republic of)                                          ..                         ..              ..                     ..
Maldives                                                            ..                         ..              ..                     ..
Nepal                                                            24.0                       12.4        3 364 139                    8.1
Pakistan                                                         11.0                        6.8               ..                     ..
Sri Lanka                                                           ..                         ..              ..                     ..
                                                                                                                                        
Western Asia
Armenia                                                          33.1                       25.1               ..                     ..
Azerbaijan                                                       24.4                          ..              ..                     ..
Bahrain                                                             ..                         ..              ..                     ..
Cyprus                                                              ..                         ..         44 752                  25.5
Georgia                                                             ..                         ..        728 950                  29.1
S t a t is t ic a l a n n ex

                                                                                                    121
TABLE A5 (cont.)

                                      Share of rural households                Agricultural holders
                                       that are female headed
                                                 (%)                    (Thousands)                 (% of total)

                                   Most recent           Earliest           Total                   Female share
                                   observation         observation


Iraq                                      ..                  ..                 ..                         ..
Israel                                    ..                  ..                 ..                         ..
Jordan                                 10.9                 9.0            91 585                         3.0
Kuwait                                    ..                  ..                 ..                         ..
Lebanon (2)                               ..                  ..          194 264                         7.1
Occupied Palestinian Territory            ..                  ..                 ..                         ..
Oman                                      ..                  ..                 ..                         ..
Qatar                                     ..                  ..                 ..                         ..
Saudi Arabia                              ..                  ..          242 267                         0.8
Syrian Arab Republic                      ..                  ..                 ..                         ..
Turkey                                   9.1                8.6                  ..                         ..
United Arab Emirates                      ..                  ..                 ..                         ..
Yemen                                    9.5               12.8                  ..                         ..


LATIN AMERICA AND THE CARIBBEAN


Caribbean
Anguilla                                  ..                  ..                 ..                         ..
Antigua and Barbuda                       ..                  ..                 ..                         ..
Aruba                                     ..                  ..                 ..                         ..
Bahamas                                   ..                  ..                 ..                         ..
Barbados                                  ..                  ..                 ..                         ..
British Virgin Islands                    ..                  ..                 ..                         ..
Cayman Islands                            ..                  ..                 ..                         ..
Cuba                                      ..                  ..                 ..                         ..
Dominica                                  ..                  ..                 ..                         ..
Dominican Republic (B)                 29.7                18.0           243 104                        10.2
Grenada                                   ..                  ..                 ..                         ..
Guadeloupe                                ..                  ..                 ..                         ..
Haiti                                  38.6                32.9                  ..                         ..
Jamaica (B)                               ..                  ..          182 169                        19.3
Martinique                                ..                  ..                 ..                         ..
Montserrat                                ..                  ..                 ..                         ..
Netherlands Antilles                      ..                  ..                 ..                         ..
Puerto Rico                               ..                  ..           17 659                         8.8
Saint Kitts & Nevis                       ..                  ..            3 046                        27.9
Saint Lucia                               ..                  ..                 ..                         ..
Saint Vincent and the Grenadines          ..                  ..                 ..                         ..
Trinidad & Tobago                         ..                  ..           19 051                        14.7
Turks and Caicos Islands                  ..                  ..                 ..                         ..
United States Virgin Islands              ..                  ..                 ..                         ..
122                 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A5 (cont.)

                                                               Share of rural households                    Agricultural holders
                                                                that are female headed
                                                                             (%)                      (Thousands)          (% of total)

                                                           Most recent                    Earliest       Total            Female share
                                                           observation                  observation


Central America
Belize (B)                                                          ..                         ..        9 697                     8.1
Costa Rica                                                          ..                         ..            ..                     ..
El Salvador                                                         ..                         ..            ..                     ..
Guatemala                                                        16.1                       18.0       819 162                     7.8
Honduras                                                         20.2                          ..            ..                     ..
Mexico                                                              ..                         ..            ..                     ..
Nicaragua                                                        19.3                       20.0       196 909                  18.1
Panama (B)                                                          ..                         ..      232 464                  29.3


South America
Argentina (B)                                                       ..                         ..      202 423                  18.2
Bolivia (Plurinational State of)                                 17.1                       17.3             ..                     ..
Brazil   (1)
                                                                 13.7                       16.8             ..                     ..
Chile (B)                                                           ..                         ..      268 787                  29.9
Colombia                                                         21.7                       16.7             ..                     ..
Ecuador                                                             ..                         ..      842 882                  25.4
Falkland Islands (Malvinas)                                         ..                         ..            ..                     ..
French Guiana                                                       ..                         ..            ..                     ..
Guyana                                                              ..                         ..            ..                     ..
Paraguay                                                         13.4                          ..            ..                     ..
Peru   (B)
                                                                 16.3                       13.3      1 750 640                 20.4
Suriname                                                            ..                         ..            ..                     ..
Uruguay (B)                                                         ..                         ..       49 302                  18.1
Venezuela (Bolivarian Republic of)                                  ..                         ..            ..                     ..
                                                                                                                                      
OCEANIA EXCLUDING AUSTRALIA AND
NEW ZEALAND
American Samoa                                                      ..                         ..        7 094                  20.6
Cook Islands                                                        ..                         ..            ..                     ..
Fiji                                                                ..                         ..            ..                     ..
French Polynesia                                                    ..                         ..            ..                     ..
Guam                                                                ..                         ..            ..                     ..
Kiribati                                                            ..                         ..            ..                     ..
Marshall Islands                                                    ..                         ..            ..                     ..
Micronesia (Federated States of)                                    ..                         ..            ..                     ..
Nauru                                                               ..                         ..            ..                     ..
New Caledonia                                                       ..                         ..            ..                     ..
Niue                                                                ..                         ..            ..                     ..
Northern Mariana Islands                                            ..                         ..          214                     9.3
Palau                                                               ..                         ..            ..                     ..
Papua New Guinea                                                    ..                         ..            ..                     ..
Samoa                                                               ..                         ..       14 778                     1.7
S t a t is t ic a l a n n ex

                                                                                                  123
TABLE A5 (cont.)

                                    Share of rural households                Agricultural holders
                                     that are female headed
                                               (%)                    (Thousands)                 (% of total)

                                 Most recent           Earliest           Total                   Female share
                                 observation         observation


Solomon Islands                         ..                  ..                 ..                         ..
Tokelau                                 ..                  ..                 ..                         ..
Tonga                                   ..                  ..                 ..                         ..
Tuvalu                                  ..                  ..                 ..                         ..
Vanuatu                                 ..                  ..                 ..                         ..
Wallis and Futuna Islands               ..                  ..                 ..                         ..
                                                                                                            
COUNTRIES IN DEVELOPED REGIONS
                                                                                                            
ASIA AND OCEANIA
Australia                               ..                  ..                 ..                         ..
Japan                                   ..                  ..                 ..                         ..
New Zealand                             ..                  ..                 ..                         ..


EUROPE


Eastern Europe
Belarus                                 ..                  ..                 ..                         ..
Bulgaria                                ..                  ..                 ..                         ..
Czech Republic                          ..                  ..                 ..                         ..
Czechoslovakia                          ..                  ..                 ..                         ..
Hungary                                 ..                  ..          958 534                        23.9
Poland                                  ..                  ..                 ..                         ..
Republic of Moldova                  30.8                   ..                 ..                         ..
Romania                                 ..                  ..                 ..                         ..
Russian Federation                      ..                  ..                 ..                         ..
Slovakia                                ..                  ..                 ..                         ..
Ukraine                              47.9                   ..                 ..                         ..
USSR                                    ..                  ..                 ..                         ..
Yugoslav SFR                            ..                  ..                 ..                         ..


Northern Europe                                                         703 649                        12.0
Denmark (7)                             ..                  ..           57 310                         8.7
Estonia                                 ..                  ..                 ..                         ..
Faroe Islands                           ..                  ..                 ..                         ..
Finland (7)                             ..                  ..           75 740                        10.8
Iceland (7)                             ..                  ..                 ..                         ..
Ireland (7)                             ..                  ..          141 340                        10.7
Latvia                                  ..                  ..                 ..                         ..
Lithuania                               ..                  ..                 ..                         ..
Norway (7)                              ..                  ..           69 959                        12.9
Sweden (7)                              ..                  ..           75 910                        10.0
United Kingdom (B)                      ..                  ..          283 390                        18.8
124                       TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A5 (cont.)

                                                                     Share of rural households                    Agricultural holders
                                                                      that are female headed
                                                                                   (%)                      (Thousands)          (% of total)

                                                                 Most recent                    Earliest       Total            Female share
                                                                 observation                  observation


Southern Europe
Albania                                                                   ..                         ..            ..                     ..
Andorra                                                                   ..                         ..            ..                     ..
Bosnia and Herzegovina                                                    ..                         ..            ..                     ..
Croatia                                                                   ..                         ..            ..                     ..
Gibraltar                                                                 ..                         ..            ..                     ..
Greece (7)                                                                ..                         ..      816 530                  25.1
Holy See                                                                  ..                         ..            ..                     ..
Italy   (B)
                                                                          ..                         ..     1 663 510                 32.2
Malta                                                                     ..                         ..            ..                     ..
Montenegro                                                                ..                         ..            ..                     ..
Portugal      (7)
                                                                          ..                         ..      409 308                  23.2
San Marino                                                                ..                         ..            ..                     ..
Serbia                                                                    ..                         ..      778 891                  18.1
Serbia and Montenegro                                                     ..                         ..            ..                     ..
Slovenia                                                                  ..                         ..            ..                     ..
Spain (B)                                                                 ..                         ..      988 060                  28.8
The former Yugoslav Republic of Macedonia                                 ..                         ..            ..                     ..


Western Europe                                                                                              1 219 730                 17.3
Austria (7)                                                               ..                         ..      194 910                  29.5
Belgium (7)                                                               ..                         ..       59 280                  15.0
Belgium-Luxembourg                                                        ..                         ..            ..                     ..
France (B)                                                                ..                         ..      427 630                  23.1
Germany (7)                                                               ..                         ..      440 060                     8.8
Liechtenstein                                                             ..                         ..            ..                     ..
Luxembourg (7)                                                            ..                         ..        2 750                  19.6
Monaco                                                                    ..                         ..            ..                     ..
Netherlands         (7)
                                                                          ..                         ..       95 100                     7.8
Switzerland                                                               ..                         ..            ..                     ..


NORTHERN AMERICA
Bermuda                                                                   ..                         ..            ..                     ..
Canada                                                                    ..                         ..            ..                     ..
Greenland                                                                 ..                         ..            ..                     ..
Saint Pierre and Miquelon                                                 ..                         ..            ..                     ..
United States of America                                                  ..                         ..            ..                     ..
S t a t is t ic a l a n n ex

                                                                                                                     125
Table A6
Share of adult population with chronic energy deficiency (CED – body mass index less than 18.5) by sex and
share of children underweight by sex, residence and household wealth quintile, most recent observations

                                      Share of adult                                Share of children
                                   population with CED                                underweight
                                        (% of total)                                    (% of total)

                                                                    By sex            By residence               By household
                                                                                                                 wealth quintile
                                    Women         Men       Male         Female     Urban         Rural        Poorest    Richest


WORLD


COUNTRIES IN DEVELOPING REGIONS                             18.0             17.3    14.0          19.6


AFRICA                               12.5                   20.6             19.2    14.5          20.8          27.8       13.5


Sub-Saharan Africa                   13.0                   23.1             21.6    16.8          24.0          28.8       15.3


Eastern Africa                       14.5                   27.6             25.3    19.3          27.3          32.3       15.5
Burundi                                 ..             ..      ..              ..    22.0          41.0              ..       ..
Comoros                              10.3              ..   28.0             21.0       ..             ..            ..       ..
Djibouti (1)                            ..             ..   34.0             33.0    30.0          42.0              ..       ..
Eritrea                              37.3              ..   41.0             39.0    29.0          45.0          49.0       20.0
Ethiopia (C)                         26.5          36.7     39.0             38.0    23.0          40.0          43.0       29.0
Ethiopia PDR                            ..             ..      ..              ..       ..             ..            ..       ..
Kenya     (1)
                                     12.3              ..   23.0             19.0    23.0          13.0              ..       ..
Madagascar                           19.2              ..   41.0             38.0    35.0          41.0          46.0       29.0
Malawi                                9.2              ..   20.0             19.0    16.0          20.0          23.0       14.0
Mauritius                               ..             ..      ..              ..       ..             ..            ..       ..
Mozambique                            8.6              ..   20.0             15.0    13.0          19.0          23.0        7.0
Réunion                                 ..             ..      ..              ..       ..             ..            ..       ..
Rwanda                                9.8              ..   23.0             22.0    16.0          24.0          31.0       10.0
Seychelles                              ..             ..      ..              ..       ..             ..            ..       ..
Somalia                                 ..             ..   37.0             34.0    23.0          43.0          48.0       16.0
Uganda                               12.1              ..   21.0             20.0    14.0          21.0          25.0       11.0
United Republic of Tanzania          10.4              ..   22.0             22.0    17.0          23.0          25.0       12.0
Zambia                                9.6              ..   21.0             18.0    17.0          20.0          21.0       14.0
Zimbabwe (C)                          9.2          15.5     17.0             16.0    11.0          18.0          21.0        9.0


Middle Africa                        13.4                   23.3             21.2    18.2          25.4          29.8       14.5
Angola                                  ..             ..   32.0             29.0    30.0          32.0              ..       ..
Cameroon                              6.7              ..   21.0             17.0    11.0          26.0          35.0        6.0
Central African Republic             15.3              ..   31.0             26.0    26.0          30.0          30.0       22.0
Chad                                 20.3              ..   37.0             37.0    30.0          38.0          48.0       29.0
Congo                                13.2              ..   15.0             14.0    10.0          18.0          19.0        5.0
Democratic Republic of the Congo     18.5              ..   33.0             30.0    24.0          36.0          34.0       20.0
Equatorial Guinea                       ..             ..   19.0             18.0    15.0          21.0              ..       ..
Gabon                                 6.6              ..   13.0             11.0    10.0          17.0              ..       ..
Sao Tome and Principe                   ..             ..    9.0              9.0     8.0          11.0          13.0        5.0
126               TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A6 (cont.)

                                                  Share of adult                                           Share of children
                                               population with CED                                           underweight
                                                      (% of total)                                            (% of total)

                                                                                           By sex            By residence           By household
                                                                                                                                    wealth quintile
                                                 Women           Men            Male            Female     Urban       Rural       Poorest   Richest


Northern Africa                                                                  10.3                9.7     5.3             8.0    16.8        8.0
Algeria                                                ..             ..          4.0                4.0     3.0             4.0     5.0        3.0
Egypt                                                1.6             3.2          8.0                7.0     7.0             8.0     9.0        7.0
Libyan Arab Jamahiriya                                 ..             ..          5.0                4.0     4.0             6.0       ..        ..
Morocco     (C)
                                                     7.3             5.7         10.0               10.0     7.0        14.0        17.0        4.0
Sudan                                                  ..             ..         32.0               30.0       ..             ..    36.0       18.0
Tunisia                                                ..             ..          3.0                3.0       ..             ..       ..        ..
Western Sahara                                         ..             ..              ..              ..       ..             ..       ..        ..


Southern Africa                                      7.8                         14.4               14.2    12.0        15.2
Botswana                                               ..             ..         13.0               13.0    12.0        14.0           ..        ..
Lesotho                                              5.7              ..         19.0               21.0    16.0        20.0        27.0       11.0
Namibia                                            15.9               ..         21.0               21.0    15.0        25.0        27.0        9.0
South Africa                                         6.2         12.5            13.0               11.0    12.0        11.0           ..        ..
Swaziland                                            3.2         10.1             6.0                5.0     5.0             6.0     8.0        4.0


Western Africa                                     12.9                          27.1               25.8    17.7        28.1        32.4       15.8
Benin                                                9.2              ..         24.0               21.0    18.0        25.0           ..        ..
Burkina Faso                                       20.8               ..         38.0               37.0    26.0        41.0        44.0       24.0
Cape Verde (1)                                         ..             ..              ..              ..     9.0             9.0       ..        ..
Côte d’Ivoire                                        8.2              ..         22.0               19.0    13.0        24.0        26.0       10.0
Gambia                                                 ..             ..         21.0               20.0    15.0        23.0        26.0       14.0
Ghana (C)                                            8.6         16.2            18.0               17.0    12.0        21.0        25.0        8.0
Guinea                                             13.2               ..         27.0               26.0    20.0        29.0        30.0       24.0
Guinea-Bissau                                          ..             ..         19.0               20.0    13.0        22.0        21.0       10.0
Liberia                                            10.0               ..         25.0               23.0    21.0        25.0        27.0       18.0
Mali                                               13.5               ..         33.0               31.0       ..             ..       ..        ..
Mauritania                                         13.0               ..         31.0               29.0    20.0        37.0        40.0       13.0
Niger                                              19.2               ..         45.0               44.0    27.0        47.0        48.0       30.0
Nigeria                                            12.2               ..         29.0               28.0    22.0        32.0        35.0       13.0
Saint Helena                                           ..             ..              ..              ..       ..             ..       ..        ..
Senegal                                            18.2               ..         16.0               18.0    10.0        22.0        26.0        6.0
Sierra Leone                                       11.2               ..         32.0               29.0    23.0        33.0        36.0       21.0
Togo                                               10.9               ..         27.0               25.0    16.0        32.0        37.0       15.0


ASIA EXCLUDING JAPAN                               13.3                          15.6               19.4    14.7        19.5


Central Asia                                         6.9                          8.6                7.8     7.4             8.4     9.6        5.2
Kazakhstan                                           7.4              ..          4.0                4.0     3.0             5.0     5.0        1.0
Kyrgyzstan                                           4.2             3.2          4.0                3.0     3.0             3.0     3.0        3.0
Tajikistan                                             ..             ..         18.0               17.0    17.0        17.0        22.0       14.0
S t a t is t ic a l a n n ex

                                                                                                                                 127
TABLE A6 (cont.)

                                               Share of adult                                 Share of children
                                            population with CED                                 underweight
                                                 (% of total)                                     (% of total)

                                                                              By sex            By residence               By household
                                                                                                                           wealth quintile
                                             Women         Men        Male         Female     Urban         Rural        Poorest     Richest


Turkmenistan                                   9.9               ..   12.0             10.0     9.0          12.0          12.0        5.0
Uzbekistan                                     5.9              3.8    5.0              5.0     5.0              5.0           6.0     3.0


Eastern Asia excluding Japan                   6.3              6.0                             4.0              8.0
China   (C)
                                               8.5              9.2      ..              ..     2.0              9.0            ..       ..
China, Hong Kong SAR                             ..              ..      ..              ..       ..              ..            ..       ..
China, Macao SAR                                 ..              ..      ..              ..       ..              ..            ..       ..
China, mainland                                  ..              ..      ..              ..       ..              ..            ..       ..
Democratic People’s Republic of Korea (2)        ..              ..   24.0             23.0       ..              ..            ..       ..
Mongolia                                       3.9              5.9    6.0              7.0     6.0              7.0           8.0     4.0
Republic of Korea                              6.5              2.8      ..              ..       ..              ..            ..       ..


Southeastern Asia                             18.2          14.1      25.3             25.3    23.4          30.4
Brunei Darussalam                                ..              ..      ..              ..       ..              ..            ..       ..
Cambodia                                      16.1               ..   35.0             36.0    35.0          36.0          43.0       23.0
Indonesia                                        ..              ..      ..              ..    25.0          30.0               ..       ..
Lao People’s Democratic Republic              14.8          12.1      37.0             38.0    26.0          39.0          44.0       18.0
Malaysia                                      10.0              9.2   19.0             19.0    16.0          23.0               ..       ..
Myanmar                                          ..              ..   31.0             32.0    25.0          34.0               ..       ..
Philippines                                   14.2          10.6         ..              ..       ..              ..            ..       ..
Singapore                                     14.6              4.4    4.0              3.0       ..              ..            ..       ..
Thailand                                       9.6          11.6       9.0             10.0     6.0          11.0          15.0        4.0
Timor-Leste                                   37.7          26.4      46.0             45.0    42.0          48.0          18.0       10.0
Viet Nam                                      28.3          24.4      21.0             19.0    12.0          22.0          29.0       10.0
 
Southern Asia                                 23.8                    32.9             33.4    30.3          39.3
Afghanistan (1)                                  ..              ..   38.0             40.0    47.0          50.0               ..       ..
Bangladesh                                    29.7               ..   44.0             49.0    40.0          48.0          56.0       32.0
Bhutan                                           ..              ..   20.0             17.0       ..              ..            ..       ..
India                                         35.6          33.7      46.0             49.0    38.0          51.0          61.0       25.0
Iran (Islamic Republic of)                     5.4              6.0   12.0             10.0    10.0          14.0               ..       ..
Maldives                                         ..              ..   31.0             30.0       ..              ..            ..       ..
Nepal                                         24.4               ..   38.0             40.0    23.0          41.0          47.0       19.0
Pakistan                                      31.6          30.8      38.0             36.0    35.0          39.0               ..       ..
Sri Lanka (3)                                 16.2               ..   29.0             30.0    19.0          32.0               ..       ..


Western Asia                                                          11.4             11.1
Armenia                                        5.2               ..    2.0              6.0     4.0              4.0           5.0     1.0
Azerbaijan                                     4.8              2.1    9.0             10.0     6.0          13.0          17.0        4.0
Bahrain                                          ..              ..    7.0             11.0       ..              ..            ..       ..
Cyprus                                         6.9              1.7      ..              ..       ..              ..            ..       ..
128                   TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A6 (cont.)

                                                      Share of adult                                           Share of children
                                                   population with CED                                           underweight
                                                          (% of total)                                            (% of total)

                                                                                               By sex            By residence           By household
                                                                                                                                        wealth quintile
                                                     Women           Men            Male            Female     Urban       Rural       Poorest   Richest


Georgia                                                    ..             ..          2.0                2.0     2.0             3.0     3.0        2.0
Iraq                                                       ..             ..          8.0                7.0     7.0             8.0       ..        ..
Israel                                                     ..             ..              ..              ..       ..             ..       ..        ..
Jordan                                                   3.9              ..          4.0                5.0     4.0             7.0       ..        ..
Kuwait                                                   2.3             2.7         10.0                9.0       ..             ..       ..        ..
Lebanon                                                    ..             ..              ..              ..       ..             ..       ..        ..
Occupied Palestinian Territory                             ..             ..          3.0                3.0     3.0             3.0       ..        ..
Oman                                                       ..             ..         18.0               18.0       ..             ..       ..        ..
Qatar (2)                                                  ..             ..          7.0                5.0       ..             ..       ..        ..
Saudi Arabia                                             4.9             5.9         17.0               12.0       ..             ..       ..        ..
Syrian Arab Republic                                       ..             ..         11.0                9.0     9.0        10.0        13.0        8.0
Turkey (C)                                               1.6             1.5              ..              ..     2.0             5.0       ..        ..
United Arab Emirates                                   10.0               ..         16.0               13.0       ..             ..       ..        ..
Yemen                                                  25.2               ..         46.0               45.0    37.0        48.0           ..        ..


LATIN AMERICA AND THE CARIBBEAN


Caribbean
Anguilla                                                   ..             ..              ..              ..       ..             ..       ..        ..
Antigua and Barbuda                                        ..             ..              ..              ..       ..             ..       ..        ..
Aruba                                                      ..             ..              ..              ..       ..             ..       ..        ..
Bahamas                                                    ..             ..              ..              ..       ..             ..       ..        ..
Barbados                                                 3.3             3.1              ..              ..       ..             ..       ..        ..
British Virgin Islands                                     ..             ..              ..              ..       ..             ..       ..        ..
Cayman Islands                                             ..             ..              ..              ..       ..             ..       ..        ..
Cuba                                                     6.2             5.3              ..              ..     4.0             5.0       ..        ..
Dominica                                                   ..             ..              ..              ..       ..             ..       ..        ..
Dominican Republic                                       5.1              ..          4.0                4.0     4.0             5.0     7.0        2.0
Grenada                                                    ..             ..              ..              ..       ..             ..       ..        ..
Guadeloupe                                                 ..             ..              ..              ..       ..             ..       ..        ..
Haiti                                                  15.5               ..         22.0               22.0    15.0        26.0        27.0        8.0
Jamaica                                                    ..             ..          4.0                4.0       ..            5.0       ..        ..
Martinique                                                 ..             ..              ..              ..       ..             ..       ..        ..
Montserrat                                                 ..             ..              ..              ..       ..             ..       ..        ..
Netherlands Antilles                                       ..             ..              ..              ..       ..             ..       ..        ..
Puerto Rico                                                ..             ..              ..              ..       ..             ..       ..        ..
Saint Kitts & Nevis                                        ..             ..              ..              ..       ..             ..       ..        ..
Saint Lucia                                                ..             ..              ..              ..       ..             ..       ..        ..
Saint Vincent and the Grenadines                           ..             ..              ..              ..       ..             ..       ..        ..
Trinidad & Tobago                                          ..             ..          7.0                5.0       ..             ..       ..        ..
Turks and Caicos Islands                                   ..             ..              ..              ..       ..             ..       ..        ..
United States Virgin Islands                               ..             ..              ..              ..       ..             ..       ..        ..
S t a t is t ic a l a n n ex

                                                                                                                          129
TABLE A6 (cont.)

                                        Share of adult                                 Share of children
                                     population with CED                                 underweight
                                          (% of total)                                     (% of total)

                                                                       By sex            By residence               By household
                                                                                                                    wealth quintile
                                      Women         Men        Male         Female     Urban         Rural        Poorest     Richest


Central America                         2.9                     9.8              9.9     6.9          12.9
Belize                                    ..              ..    5.0              7.0     4.0              8.0            ..       ..
Costa Rica (2)                            ..              ..    6.0              4.0     4.0              7.0            ..       ..
El Salvador                               ..              ..   10.0             11.0     7.0          13.0               ..       ..
Guatemala (3)                           2.0               ..   23.0             23.0    16.0          26.0               ..       ..
Honduras                                4.0               ..   11.0             12.0     6.0          15.0          22.0        2.0
Mexico                                  1.4              1.5    8.0              7.0     6.0          12.0               ..       ..
Nicaragua                               3.7               ..    7.0              7.0     5.0              9.0       11.0        2.0
Panama                                  3.6              2.6    8.0              8.0       ..              ..            ..       ..


South America                                                   7.2              6.9     5.4              9.9
Argentina (1)                           3.4               ..      ..              ..       ..              ..            ..       ..
Bolivia (Plurinational State of)        2.0               ..    6.0              6.0     4.0              9.0            ..       ..
Brazil (C)                              3.5              2.8    6.0              5.0     5.0              9.0            ..       ..
Chile (2)                               1.1              0.6      ..              ..       ..              ..            ..       ..
Colombia (3)                            3.9              3.7    7.0              7.0     6.0          10.0          12.0        3.0
Ecuador                                   ..              ..    9.0             10.0     8.0          11.0               ..       ..
Falkland Islands (Malvinas)               ..              ..      ..              ..       ..              ..            ..       ..
French Guiana                             ..              ..      ..              ..       ..              ..            ..       ..
Guyana                                    ..              ..   14.0             13.0    10.0          15.0               ..       ..
Paraguay                                  ..              ..    5.0              3.0     3.0              6.0           9.0     0.0
Peru                                    1.9               ..    6.0              5.0     2.0              9.0       12.0        1.0
Suriname                                  ..              ..   10.0             10.0       ..              ..       12.0        8.0
Uruguay                                   ..              ..    4.0              5.0       ..              ..            ..       ..
Venezuela (Bolivarian Republic of)        ..              ..    5.0              5.0       ..              ..            ..       ..
 
OCEANIA EXCLUDING AUSTRALIA AND
NEW ZEALAND
American Samoa                          0.2               ..      ..              ..       ..              ..            ..       ..
Cook Islands                              ..              ..      ..              ..       ..              ..            ..       ..
Fiji                                    5.6              6.6     ..               ..       ..              ..            ..       ..
French Polynesia                          ..              ..     ..               ..       ..              ..            ..       ..
Guam                                      ..              ..     ..               ..       ..              ..            ..       ..
Kiribati                                0.6              0.3     ..               ..       ..              ..            ..       ..
Marshall Islands                          ..              ..     ..               ..       ..              ..            ..       ..
Micronesia (Federated States of)          ..              ..     ..               ..       ..              ..            ..       ..
Nauru                                     ..              ..     ..               ..       ..              ..            ..       ..
New Caledonia                             ..              ..     ..               ..       ..              ..            ..       ..
Niue                                      ..              ..     ..               ..       ..              ..            ..       ..
Northern Mariana Islands                  ..              ..     ..               ..       ..              ..            ..       ..
Palau                                     ..              ..     ..               ..       ..              ..            ..       ..
Papua New Guinea    (1)
                                          ..              ..   28.0             25.0    18.0          28.0               ..       ..
Samoa                                     ..              ..      ..              ..       ..              ..            ..       ..
130                  TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1




TABLE A6 (cont.)

                                                     Share of adult                                           Share of children
                                                  population with CED                                           underweight
                                                         (% of total)                                            (% of total)

                                                                                              By sex            By residence           By household
                                                                                                                                       wealth quintile
                                                    Women           Men            Male            Female     Urban       Rural       Poorest   Richest


Solomon Islands                                           ..             ..              ..              ..       ..             ..       ..        ..
Tokelau                                                   ..             ..              ..              ..       ..             ..       ..        ..
Tonga                                                     ..             ..              ..              ..       ..             ..       ..        ..
Tuvalu                                                    ..             ..              ..              ..       ..             ..       ..        ..
Vanuatu                                                 2.9             1.0         18.0               13.0    15.0        16.0        18.0       13.0
Wallis and Futuna Islands                                 ..             ..              ..              ..       ..             ..       ..        ..


COUNTRIES IN DEVELOPED REGIONS


ASIA AND OCEANIA                                        5.1             2.3
Australia                                               2.8             1.3              ..              ..       ..             ..       ..        ..
Japan                                                 10.8              4.3              ..              ..       ..             ..       ..        ..
New Zealand                                             1.6             1.3              ..              ..       ..             ..       ..        ..


EUROPE


Eastern Europe                                          4.9             1.1
Belarus                                                   ..             ..          1.0                1.0     1.0             2.0     2.0        1.0
Bulgaria                                                5.9             1.6              ..              ..       ..             ..       ..        ..
Czech Republic                                          3.7             1.0              ..              ..       ..             ..       ..        ..
Czechoslovakia                                            ..             ..              ..              ..       ..             ..       ..        ..
Hungary                                                 3.0             0.4              ..              ..       ..             ..       ..        ..
Poland                                                  3.2             1.0              ..              ..       ..             ..       ..        ..
Republic of Moldova                                     5.9              ..          3.0                5.0     3.0             5.0     7.0        1.0
Romania                                                 4.8             1.1          3.0                3.0     3.0             3.0       ..        ..
Russian Federation                                        ..             ..          3.0                3.0       ..             ..       ..        ..
Slovakia                                                7.4             1.6              ..              ..       ..             ..       ..        ..
Ukraine (4)                                             5.4              ..          1.0                1.0       ..             ..       ..        ..
USSR                                                      ..             ..              ..              ..       ..             ..       ..        ..
Yugoslav SFR                                              ..             ..              ..              ..       ..             ..       ..        ..


Northern Europe                                         3.9             1.7
Denmark                                                 3.7             0.8              ..              ..       ..             ..       ..        ..
Estonia                                                 4.4             1.3              ..              ..       ..             ..       ..        ..
Faroe Islands                                             ..             ..              ..              ..       ..             ..       ..        ..
Finland                                                 3.1             1.6              ..              ..       ..             ..       ..        ..
Iceland                                                 3.0             1.6              ..              ..       ..             ..       ..        ..
Ireland                                                 1.0             2.0              ..              ..       ..             ..       ..        ..
Latvia                                                  5.3             1.2              ..              ..       ..             ..       ..        ..
Lithuania                                               3.0             1.6              ..              ..       ..             ..       ..        ..
Norway                                                  7.0             2.0              ..              ..       ..             ..       ..        ..
S t a t is t ic a l a n n ex

                                                                                                                                131
TABLE A6 (cont.)

                                               Share of adult                                Share of children
                                            population with CED                                underweight
                                                 (% of total)                                    (% of total)

                                                                              By sex           By residence               By household
                                                                                                                          wealth quintile
                                             Women         Men        Male         Female    Urban         Rural        Poorest     Richest


Sweden                                         3.0              1.0      ..             ..       ..              ..            ..       ..
United Kingdom                                 5.9              4.1      ..             ..       ..              ..            ..       ..


Southern Europe
Albania                                          ..              ..    8.0             7.0     5.0              9.0       13.0        3.0
Andorra                                          ..              ..      ..             ..       ..              ..            ..       ..
Bosnia and Herzegovina                           ..              ..    2.0             1.0     2.0              1.0           3.0     2.0
Croatia                                        0.2              0.1      ..             ..       ..              ..            ..       ..
Gibraltar                                        ..              ..      ..             ..       ..              ..            ..       ..
Greece                                           ..              ..      ..             ..       ..              ..            ..       ..
Holy See                                         ..              ..      ..             ..       ..              ..            ..       ..
Italy                                          5.8              0.9      ..             ..       ..              ..            ..       ..
Malta                                          3.8              1.3      ..             ..       ..              ..            ..       ..
Montenegro                                       ..              ..    4.0             2.0     3.0              2.0           6.0     2.0
Portugal                                       3.4              0.9     ..              ..       ..              ..            ..       ..
San Marino                                       ..              ..     ..              ..       ..              ..            ..       ..
Serbia                                           ..              ..    2.0             2.0     2.0              1.0           4.0     2.0
Serbia and Montenegro                            ..              ..     ..              ..       ..              ..            ..       ..
Slovenia                                         ..              ..     ..              ..       ..              ..            ..       ..
Spain                                          3.0              0.5     ..              ..       ..              ..            ..       ..
The former Yugoslav Republic of Macedonia      6.4               ..    2.0             2.0     2.0              2.0           4.0     1.0


Western Europe
Austria                                        4.0              1.0     ..              ..       ..              ..            ..       ..
Belgium                                        5.3              2.6     ..              ..       ..              ..            ..       ..
Belgium-Luxembourg                               ..              ..     ..              ..       ..              ..            ..       ..
France                                           ..              ..     ..              ..       ..              ..            ..       ..
Germany                                          ..              ..     ..              ..       ..              ..            ..       ..
Liechtenstein                                    ..              ..     ..              ..       ..              ..            ..       ..
Luxembourg                                       ..              ..     ..              ..       ..              ..            ..       ..
Monaco                                           ..              ..     ..              ..       ..              ..            ..       ..
Netherlands                                      ..              ..     ..              ..       ..              ..            ..       ..
Switzerland                                    5.9              1.0     ..              ..       ..              ..            ..       ..


NORTHERN AMERICA                               3.7              1.4
Bermuda                                          ..              ..     ..              ..       ..              ..            ..       ..
Canada                                         4.1              1.2     ..              ..       ..              ..            ..       ..
Greenland                                        ..              ..     ..              ..       ..              ..            ..       ..
Saint Pierre and Miquelon                        ..              ..     ..              ..       ..              ..            ..       ..
United States of America   (5)
                                               3.3              1.5    2.0             1.0       ..              ..            ..       ..
Women in Agriculture - Making a Strong Case for Investing in Women
•	References
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      Special chapters of
      The State of Food and Agriculture
      In addition to the usual review of the recent world food and agricultural situation,
      each issue of this report since 1957 has included one or more special studies on problems
      of longer-term interest. Special chapters in earlier issues have covered the following
      subjects:

      1957	    Factors influencing the trend of food consumption
      	        Postwar changes in some institutional factors affecting agriculture
      1958	    Food and agricultural developments in Africa south of the Sahara
      	        The growth of forest industries and their impact on the world’s forests
      1959	    Agricultural incomes and levels of living in countries at different stages of
               economic development
      	        Some general problems of agricultural development in less-developed
               countries in the light of postwar experience
      1960	    Programming for agricultural development
      1961	    Land reform and institutional change
               Agricultural extension, education and research in Africa, Asia
               and Latin America
      1962	    The role of forest industries in the attack on economic underdevelopment
               The livestock industry in less-developed countries
      1963	    Basic factors affecting the growth of productivity in agriculture
      	        Fertilizer use: spearhead of agricultural development
      1964	    Protein nutrition: needs and prospects
      	        Synthetics and their effects on agricultural trade
      1966	    Agriculture and industrialization
      	        Rice in the world food economy
      1967	    Incentives and disincentives for farmers in developing countries
      	        The management of fishery resources
      1968	    Raising agricultural productivity in developing countries through
               technological improvement
      	        Improved storage and its contribution to world food supplies
      1969	    Agricultural marketing improvement programmes:
               some lessons from recent experience
      	        Modernizing institutions to promote forestry development
      1970	    Agriculture at the threshold of the Second Development Decade
      1971	    Water pollution and its effects on living aquatic resources and fisheries
      1972	    Education and training for development
      	        Accelerating agricultural research in the developing countries
      1973	    Agricultural employment in developing countries
      1974	    Population, food supply and agricultural development
      1975	    The Second United Nations Development Decade:
               mid-term review and appraisal
      1976	    Energy and agriculture
      1977	    The state of natural resources and the human environment for food
               and agriculture
      1978	    Problems and strategies in developing regions
      1979	    Forestry and rural development
      1980	    Marine fisheries in the new era of national jurisdiction
      1981	    Rural poverty in developing countries and means of poverty alleviation
      1982	    Livestock production: a world perspective
      1983	    Women in developing agriculture
      1984	    Urbanization, agriculture and food systems
147
1985	    Energy use in agricultural production
	        Environmental trends in food and agriculture
	        Agricultural marketing and development
1986	    Financing agricultural development
1987–88	 Changing priorities for agricultural science and technology
         in developing countries
1989	    Sustainable development and natural resource management
1990	    Structural adjustment and agriculture
1991	    Agricultural policies and issues: lessons from the 1980s and prospects
         for the 1990s
1992	    Marine fisheries and the law of the sea: a decade of change
1993	    Water policies and agriculture
1994	    Forest development and policy dilemmas
1995	    Agricultural trade: entering a new era?
1996	    Food security: some macroeconomic dimensions
1997	    The agroprocessing industry and economic development
1998	    Rural non-farm income in developing countries
2000	    World food and agriculture: lessons from the past 50 years
2001	    Economic impacts of transboundary plant pests and animal diseases
2002	    Agriculture and global public goods ten years after the Earth Summit
2003–04	 Agricultural biotechnology: meeting the needs of the poor?
2005	    Agriculture trade and poverty: can trade work for the poor?
2006	    Food aid for food security?
2007	    Paying farmers for environmental services
2008	    Biofuels: prospects, risks and opportunities
2009	    Livestock in the balance
THE STATE
OF FOOD
AND
AGRICULTURE
     Women make significant contributions to the rural
     economy in all developing country regions. Their roles
     differ across regions, yet they consistently have less access
     than men to the resources and opportunities they need to
     be more productive. Increasing women’s access to land,
     livestock, education, financial services, extension, technol-
     ogy and rural employment would boost their productivity
     and generate gains in terms of agricultural production,
     food security, economic growth and social welfare. Closing
     the gender gap in agricultural inputs alone could lift 100–-
     150 million people out of hunger. No blueprint exists for
     closing the gender gap, but some basic principles are
     universal: governments, the international community and
     civil society should work together to eliminate discrimina-
     tion under the law, to promote equal access to resources
     and opportunities, to ensure that agricultural policies and
     programmes are gender-aware, and to make women’s
     voices heard as equal partners for sustainable develop-
     ment. Achieving gender equality and empowering women
     in agriculture is not only the right thing to do. It is also
     crucial for agricultural development and food security.




                    ISBN 978-92-5-106768-0    ISSN 0081-4539




                          9   789251         067680
                                               I2050E/1/01.11

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Women in Agriculture - Making a Strong Case for Investing in Women

  • 1. ISSN 0081-4539 2010-11 THE STATE OF FOOD AND AGRICULTURE WOMEN IN AGRICULTURE Closing the gender gap for development
  • 2. Photos on front cover and page 3: All photos are from the FAO Mediabase. Copies of FAO publications can be requested from: SALES AND MARKETING GROUP E-mail: [email protected] Office of Knowledge Exchange, Research and Extension Fax: (+39) 06 57053360 Food and Agriculture Organization of the United Nations Web site: http://www.fao.org/catalog/inter-e.htm Viale delle Terme di Caracalla 00153 Rome, Italy
  • 3. ISSN 0081-4539 2010-11 THE STATE OF FOOD AND AGRICULTURE FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS Rome, 2011
  • 4. The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companies or products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO in preference to others of a similar nature that are not mentioned. The designations employed and the presentation of material in the map does not imply the expression of any opinion whatsoever on the part of FAO concerning the legal or constitutional status of any country, territory or sea area, or concerning the delimitation of frontiers. ISBN 978-92-5-106768-0 All rights reserved. Reproduction and dissemination of material in this information product for educational or other non-commercial purposes are authorized without any prior written permission from the copyright holders provided the source is fully acknowledged. Reproduction of material in this information product for resale or other commercial purposes is prohibited without written permission of the copyright holders. Applications for such permission should be addressed to: Chief Electronic Publishing Policy and Support Branch Office of Knowledge Exchange, Research and Extension FAO Viale delle Terme di Caracalla, 00153 Rome, Italy or by e-mail to: [email protected] © FAO 2011
  • 5. iii Contents Foreword vi Acknowledgements viii Abbreviations and acronyms x Part I Women in agriculture: closing the gender gap for development 1 1. The gender gap in agriculture 3 Structure of the report and key messages 5 Key messages of the report 5 2. Women’s work 7 Women in agriculture 7 Women in rural labour markets 16 Key messages 22 3. Documenting the gender gap in agriculture 23 Land 23 Livestock 24 Farm labour 26 Education 28 Information and extension 32 Financial services 33 Technology 34 Key messages 36 4. Gains from closing the gender gap 39 Productivity of male and female farmers 40 Production gains from closing the gender gap 41 Other social and economic benefits of closing the gender gap 43 Key messages 45 5. Closing the gender gap in agriculture and rural employment 46 Closing the gap in access to land 46 Closing the gap in rural labour markets 49 Closing the financial services gap 51 Closing the gap in social capital through women’s groups 53 Closing the technology gap 56 Key messages 58 6. Closing the gender gap for development 61 Part II World food and agriculture in review 63 Trends in undernourishment 65 Food production, consumption and trade during the crises 68 Recent trends in agricultural prices: a higher price plateau, and greater price volatility 76 Conclusions 81
  • 6. iv PART III Statistical annex 83 Notes on the Annex tables 85 TABLE A1 Total population, female share of population and rural share of population in 1980, 1995 and 2010 90 TABLE A2 Female share of national, rural and urban population aged 15–49, most recent and earliest observations 97 TABLE A3 Economically active population, female share of economically active population and agricultural share of economically active women in 1980, 1995 and 2010 104 TABLE A4 Economically active population, agricultural share of economically active population and female share of economically active in agriculture in 1980, 1995 and 2010 111 TABLE A5 Share of households in rural areas that are female-headed, most recent and earliest observations, and total agricultural holders and female share of agricultural holders, most recent observations 118 Table A6 Share of adult population with chronic energy deficiency (CED – body mass index less than 18.5) by sex and share of children underweight by sex, residence and household wealth quintile, most recent observations 125 References 135 Special chapters of The State of Food and Agriculture 146 TABLES 1. Employment in selected high-value agro-industries 21 2. Selected examples of health insurance products targeted towards women 52 BOXES 1. Sex versus gender 4 2. Frequently asked questions about women in agriculture 8 3. Women and unpaid household responsibilities 14 4. Female farmers, household heads and data limitations 24 5. Labour productivity and hunger, nutrition and health 27 6. Women in agricultural higher education and research in Africa 30 7. Smallholder coffee production and marketing in Uganda 37 8. Targeting transfer payments to women for social benefits 44 9. Mama Lus Frut: working together for change 47 10. India’s Self Employed Women’s Association (SEWA) 54 11. Women in a sustainable rural livelihoods programme in Uganda 59 12. Food emergencies 70 13. Implied volatility as a measure of uncertainty 79 14. Price volatility and FAO’s Intergovernmental Groups on Grains and Rice 81
  • 7. v FIGURES 1. Female share of the agricultural labour force 10 2. Proportion of labour in all agricultural activities that is supplied by women 11 3. Proportion of labour for selected crops that is supplied by women 12 4. Employment by sector 17 5. Participation in rural wage employment, by gender 18 6. Conditions of employment in rural wage employment, by gender 19 7. Wage gap between men and women in urban and rural areas 20 8. Share of male and female agricultural holders in main developing regions 25 9. Rural household assets: farm size 25 10. Household livestock assets, in male- and female-headed households 26 11. Education of male and female rural household heads 28 12. Gender differences in rural primary education attendance rates 29 13. Credit use by female- and male-headed households in rural areas 33 14. Fertilizer use by female- and male-headed households 35 15. Mechanical equipment use by female- and male-headed households 36 16. Cereal yield and gender inequality 39 17. Number of undernourished people in the world, 1969–71 to 2010 66 18. Proportion of population that is undernourished in developing regions, 1969–71 to 2010 66 19. Number of undernourished people in 2010, by region 67 20. FAO Food Price Index in real terms, 1961–2010 68 21. Average annual percentage change in GDP per capita at constant prices, 2005–2010 69 22. Annual growth in global food production, consumption and trade, 2006–2010 72 23. Indices of per capita food consumption by geographic region, 2000–10 72 24. Indices of food production by economic group 73 25. Indices of food production by region, 2000–10 74 26. Indices of food export volumes by geographic region, 2000–10 75 27. Indices of food import volumes by geographic region, 2000–10 75 28. FAO Food Price Index and indices of other commodities (fruits, beverages and raw materials), October 2000–October 2010 76 29. Indices of prices of commodities included in the FAO Food Price Index (cereals, oils, dairy, meat and sugar), October 2000–October 2010 77 30. Historic annualized volatility of international grain prices 78 31. Co-movement of energy production costs: ethanol from maize versus petrol from crude oil, October 2006–October 2010 80
  • 8. vi Foreword This edition of The State of Food and The obstacles that confront women Agriculture addresses Women in agriculture: farmers mean that they achieve lower yields closing the gender gap for development. than their male counterparts. Yet women are The agriculture sector is underperforming in as good at farming as men. Solid empirical many developing countries, and one of the evidence shows that if women farmers used key reasons is that women do not have equal the same level of resources as men on the access to the resources and opportunities land they farm, they would achieve the same they need to be more productive. This yield levels. The yield gap between men and report clearly confirms that the Millennium women averages around 20–30 percent, Development Goals on gender equality and most research finds that the gap is due (MDG 3) and poverty and food security to differences in resource use. Bringing (MDG 1) are mutually reinforcing. We must yields on the land farmed by women promote gender equality and empower up to the levels achieved by men would women in agriculture to win, sustainably, the increase agricultural output in developing fight against hunger and extreme poverty. countries between 2.5 and 4 percent. I firmly believe that achieving MDG 3 can Increasing production by this amount could help us achieve MDG 1. reduce the number of undernourished Women make crucial contributions in people in the world in the order of agriculture and rural enterprises in all 12–17 percent. According to FAO’s latest developing country regions, as farmers, estimates, 925 million people are currently workers and entrepreneurs. Their roles vary undernourished. Closing the gender gap in across regions but, everywhere, women face agricultural yields could bring that number gender-specific constraints that reduce their down by as much as 100–150 million people. productivity and limit their contributions These direct improvements in agricultural to agricultural production, economic output and food security are just one part of growth and the well-being of their families, the significant gains that could be achieved communities and countries. by ensuring that women have equal access Women face a serious gender gap in to resources and opportunities. Closing access to productive resources. Women the gender gap in agriculture would put control less land than men and the land more resources in the hands of women and they control is often of poorer quality and strengthen their voice within the household their tenure is insecure. Women own fewer – a proven strategy for enhancing the food of the working animals needed in farming. security, nutrition, education and health of They also frequently do not control the children. And better fed, healthier children income from the typically small animals they learn better and become more productive manage. Women farmers are less likely than citizens. The benefits would span generations men to use modern inputs such as improved and pay large dividends in the future. seeds, fertilizers, pest control measures and The gender gap is manifest in other ways. mechanical tools. They also use less credit and Gender relations are social phenomena often do not control the credit they obtain. and it is impossible to separate women’s Finally, women have less education and less economic spheres from their household access to extension services, which make it activities. Preparing food and collecting more difficult to gain access to and use some firewood and water are time-consuming and of the other resources, such as land, credit binding constraints that must be addressed and fertilizer. These factors also prevent if women are to be able to spend their time women from adopting new technologies as in more rewarding and more productive readily as men do. The constraints women ways. Interventions must consider women face are often interrelated and need to be within their family and community contexts. addressed holistically. Making rural labour markets function better,
  • 9. vii providing labour-saving technologies and would be significant. The basic principles public goods and services, would enable are clear. We must eliminate all forms of women to contribute more effectively to, discrimination against women under the and benefit more fully from, the economic law, ensure that access to resources is more opportunities offered by agricultural equal and that agricultural policies and growth. programmes are gender-aware, and make There exists no blueprint for closing the women’s voices heard in decision-making gender gap in agriculture, as a wide range at all levels. Women must be seen as equal of inputs, assets, services and markets are partners in sustainable development. involved and the related constraints are Achieving gender equality and empowering interlinked. But with appropriate policies women is not only the right thing to do; it is based on accurate information and analysis, also crucial for agricultural development and progress can be made and the benefits food security. Jacques Diouf FAO DIRECTOR-GENERAL
  • 10. viii Acknowledgements The State of Food and Agriculture 2010–11 Ruth Vargas Hill, Ephraim Nkonya, Amber was prepared by members of the Economic Peterman, Esteban J. Quiñones and Agnes and Social Development Department of Quisumbing, (IFPRI); Christopher Coles, Priya FAO under the overall leadership of Hafez Deshingkar, Rebecca Holmes, Nicola Jones, Ghanem, Assistant Director-General, and Jonathan Mitchell and Marcella Vigneri Kostas Stamoulis, Director of the Agricultural (ODI); Diana Fletschner (Rural Development Development Economics Division (ESA). Institute) and Lisa Kenney (University of Additional guidance was provided by Marcela Washington); Christine Okali (University Villarreal, Director, and Eve Crowley, Principal of East Anglia); Jan Lundius (independent Adviser, of the Gender, Equity and Rural consultant); and Holger Seebens (KfW Employment Division (ESW); Pietro Gennari, Entwicklungsbank). Additional background Director, Statistics Division (ESS); David papers were prepared by the following FAO Hallam, Director, Trade and Markets Division staff members: Gustavo Anríquez, Yasmeen (EST); and Keith Wiebe, Principal Officer, ESA. Khwaja, Lucia Palombi (FAO Emergency The research and writing team for Part I Operations and Rehabilitation Division) and was led by Terri Raney, André Croppenstedt Paola Termine (ESW). The report also drew and Gustavo Anríquez and included Sarah on papers prepared for the FAO-IFAD-ILO Lowder, Ira Matuschke and Jakob Skoet Workshop on Gender and Rural Employment (ESA). Additional inputs were provided and synthesized by Soline de Villard and by Luisa Cruz, Ana Paula de la O Campos, Jennie Dey de Pryck. The report benefited Stefano Gerosa, Yasmeen Khwaja, Faith from two expert consultations, partially Nilsson and Panagiotis Karfakis (ESA); funded by the World Bank. In addition to Francesca Dalla Valle, Soline de Villard, many of those mentioned above, external Caroline Dookie, John Curry, Zoraida Garcia, participants included Isatou Jallow (WFP), Denis Herbel, Regina Laub, Maria Lee, Johannes Jütting (OECD), Patricia Biermayr- Yianna Lambrou, Marta Osorio, Hajnalka Jenzano (CIAT), Markus Goldstein and Petrics, Gabriel Rugalema, Libor Stloukal, Eija Pehu (World Bank), Maria Hartl and Sophie Treinen and Peter Wobst (ESW); Annina Lubbock (IFAD), Jemima Njuki (ILRI), Magdalena Blum (FAO Office of Knowledge Thelma Paris (IRRI), Patrick Webb (Tufts Exchange, Research and Extension); Holger University), and Manfred Zeller (University of Matthey (EST); Anni McLeod and Frauke Hohenheim). Hela Kochbati (Afard), Robert Kramer (FAO Animal Production and Health Mazur (Iowa State University) and others Division); Helga Josupeit, Rebecca Metzner made valuable contributions to the Global and Stefania Vannuccini (FAO Fisheries Forum on Food Security and Nutrition (FSN and Aquaculture Policy and Economic Forum) on Women in Agriculture, organized Division); Robert Mayo (ESS) and Diana by Max Blanck and Renata Mirulla (ESA). Tempelman (FAO Regional Office for Africa). We are grateful for many useful comments Ines Smyth (Oxfam), Cathy Farnworth (on received at a mini-symposium organized at behalf of IFAD), Elisenda Estruch (ESW) the International Association of Agricultural and Julian Thomas and Frank Mischler Economists Triennial Conference. (ESA) provided valuable comments. We are In addition, the final draft report was also grateful to Amy Heyman who read, reviewed by Patrick Webb (Tufts University), commented and edited the first draft of Diana Fletschner (Rural Development the report. The report was prepared in Institute), Thomas P. Thompson (IFDC), close collaboration with Agnes Quisumbing Maria Hartl (IFAD), Carmen Diana Deere and Ruth Meinzen-Dick of IFPRI and Cheryl (UCLA), Susana Lastarria-Corhiel (University Doss of Yale University. Background papers, of Wisconsin), Jo Swinnen (University of partially funded by ESW, were prepared by Leuven), Patricia Biermayr-Jenzano, Joanne Cheryl Doss; Julia Behrman, Andrew Dillon, Sandler and colleagues (UNIFEM), Barbara
  • 11. ix Stocking (Oxfam GB), Paul Munro-Faure Ramasawmy, Mukesh Srivastava, and Franco and Paul Mathieu (FAO Climate, Energy and Stefanelli (ESS); Diana Tempelman; Maria Tenure Division), Ruth Meinzen-Dick (IFPRI), Adelaide D’Arcangelo, Zoraida Garcia and Agnes Quisumbing (IFPRI), and Cheryl Doss Clara Park (ESW), and Barbara Burlingame (Yale University). The writing team is most and Marie-Claude Dop (FAO Nutrition and grateful to the workshop participants and Consumer Protection Division). other internal and external reviewers of The publication was greatly enhanced various drafts of the manuscript. by Michelle Kendrick (ESA) who provided Part II of the report was jointly authored English editorial and project management by Sarah Lowder (ESA) and Holger Matthey support. Liliana Maldonado and Paola and Merritt Cluff (EST), under the guidance di Santo (ESA) provided excellent of Jakob Skoet. Additional inputs were administrative support throughout the provided by Joshua Dewbre and Kisan Gunjal process. Translations and printing services (EST). were provided by the Meeting Programming Part III of the report was prepared by and Documentation Service of the FAO Sarah Lowder, with assistance from Brian Corporate Services, Human Resources and Carisma and Stefano Gerosa, under the Finance Department. Graphic, layout and guidance of Terri Raney. Helpful comments proofing services were provided by Flora were provided by Naman Keita, Seevalingum Dicarlo and Visiontime.
  • 12. x Abbreviations and acronyms CED chronic energy deficiency CIAT International Centre for Tropical Agriculture FFS Farmer field school FPI Food Price Index (FAO) ICTs information and communication technologies IFAD International Fund for Agricultural Development IFDC International Fertilizer Development Center IFPRI International Food Policy Research Institute ILRI International Livestock Research Institute IMF International Monetary Fund LSMS Living Standards Measurement Study MDG Millennium Development Goal NGOs non-governmental organizations NREGA National Rural Employment Guarantee Act (India) ODI Overseas Development Institute (United Kingdom) OECD Organisation for Economic Co-operation and Development RIGA Rural Income Generating Activities SIGI Social Institutions and Gender Inequality UCLA University of California, Los Angeles (United States of America) UNDP United Nations Development Programme UNIFEM United Nations Development Fund for Women WFP World Food Programme
  • 13. Part I WOMEN IN AGRICULTURE Closing the gender gap for development
  • 15. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 3 1. The gender gap in agriculture Agriculture is underperforming in many As a result, it is often assumed that developing countries for a number of interventions in areas such as technology, reasons. Among these is the fact that women infrastructure and market access have the lack the resources and opportunities they same impacts on men and women, when in need to make the most productive use of fact they may not. their time. Women are farmers, workers At the same time, building a gender and entrepreneurs, but almost everywhere perspective into agricultural policies and they face more severe constraints than projects has been made to seem more men in accessing productive resources, difficult and complex than it need be. markets and services. This “gender gap” Clarification of what is meant by gender is a hinders their productivity and reduces their good place to start (Box 1). contributions to the agriculture sector and to The last sentence in Box 1 also gives room the achievement of broader economic and for hope: gender roles can change. It is the social development goals. Closing the gender goal of this report that it will contribute to gap in agriculture would produce significant improving understanding so that appropriate gains for society by increasing agricultural policies can help foster gender equality, productivity, reducing poverty and hunger even as agriculture itself is changing. and promoting economic growth. The agriculture sector is becoming more Governments, donors and development technologically sophisticated, commercially practitioners now recognize that agriculture oriented and globally integrated; at the is central to economic growth and food same time, migration patterns and climate security – particularly in countries where a variability are changing the rural landscape significant share of the population depends across the developing world. These forces on the sector – but their commitment to pose challenges and present opportunities for gender equality in agriculture is less robust. all agricultural producers, but women face Gender issues are now mentioned in most additional legal and social barriers that limit national and regional agricultural and their ability to adapt to and benefit from food-security policy plans, but they are change. Governments and donors have made usually relegated to separate chapters on major commitments aimed at revitalizing women rather than treated as an integral agriculture in developing regions, but their part of policy and programming. Many efforts in agriculture will yield better results agricultural policy and project documents more quickly if they maximize the productive still fail to consider basic questions about the potential of women by promoting gender differences in the resources available to men equality. and women, their roles and the constraints Women, like men, can be considered they face – and how these differences might “productive resources”, but they are also be relevant to the proposed intervention. citizens who have an equal claim with men
  • 16. 4 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 BOX 1 Sex versus gender The concepts of “sex” and “gender” men and women (Moser, 1989). Being can be confusing, not least because socially determined, however, this even the experts sometimes use them distribution can be changed through inconsistently. Sex refers to the innate conscious social action, including public biological categories of male or female. policy. Every society is marked by gender Gender refers to the social roles and differences, but these vary widely by identities associated with what it means culture and can change dramatically over to be a man or a woman. Gender roles are time. Sex is biology. Gender is sociology. shaped by ideological, religious, ethnic, Sex is fixed. Gender roles change. economic and cultural factors and are a key determinant of the distribution of responsibilities and resources between Source: Quisumbing, 1996. on the protections, opportunities and empirical evidence from many different services provided by their governments countries shows that female farmers are just and the international community. Gender as efficient as their male counterparts, but equality is a Millennium Development Goal they have less land and use fewer inputs, so (MDG) in its own right, and it is directly they produce less. The potential gains that related to the achievement of the MDG could be achieved by closing the gender targets on reducing extreme poverty and gap in input use are estimated in this report hunger. Clear synergies exist between the in terms of agricultural yields, agricultural gender-equality and hunger-reduction goals. production, food security and broader Agricultural policy-makers and development aspects of economic and social welfare. practitioners have an obligation to ensure Because many of the constraints faced by that women are able to participate fully in, women are socially determined, they can and benefit from, the process of agricultural change. What is more, external pressures development. At the same time, promoting often serve as a catalyst for women to take gender equality in agriculture can help on new roles and responsibilities that can reduce extreme poverty and hunger. Equality improve their productivity and raise their for women would be good for agricultural status within households and communities. development, and agricultural development For example, the growth of modern supply should also be good for women. chains for high-value agricultural products The roles and status of women in is creating significant opportunities – and agriculture and rural areas vary widely challenges – for women in on-farm and off- by region, age, ethnicity and social class farm employment. Other forces for social and are changing rapidly in some parts and economic change can also translate into of the world. Policy-makers, donors and opportunities for women. development practitioners need information Gender-aware policy support and well- and analysis that reflect the diversity of the designed development projects can help contributions women make and the specific close the gender gap. Given existing challenges they are confronted with in order inequities, it is not enough that policies be to make gender-aware decisions about the gender-neutral; overcoming the constraints sector. faced by women requires much more. Despite the diversity in the roles and Reforms aimed at eliminating discrimination status of women in agriculture, the evidence and promoting equal access to productive and analysis presented in this report confirm resources can help ensure that women – and that women face a surprisingly consistent men – are equally prepared to cope with gender gap in access to productive assets, the challenges and to take advantage of inputs and services. A large body of the opportunities arising from the changes
  • 17. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 5 shaping the rural economy. Closing the farmers and estimates the gains that could gender gap in agriculture will benefit be achieved by closing the gender gap in women, the agriculture and rural sectors, agricultural input use. Potential gains in and society as a whole. The gains will vary agricultural yields, agricultural production, widely according to local circumstances, but food security and broader aspects of they are likely to be greater where women economic and social welfare are assessed. are more involved in agriculture and face the Chapter 5 advances specific policies and most severe constraints. programmes that can help close the gender While it seems obvious that closing the gap in agriculture and rural employment. gender gap would be beneficial, evidence The focus is on interventions that alleviate to substantiate this potential has been constraints on agricultural productivity and lacking. This edition of The State of Food rural development. and Agriculture has several goals: to bring Chapter 6 provides broader the best available empirical evidence to recommendations for closing the gender gap bear on the contributions women make and for development. the constraints they face in agricultural and rural enterprises in different regions of the world; to demonstrate how the gender gap Key messages of the report limits agricultural productivity, economic development and human well-being; to • Women make essential contributions to evaluate critically interventions aimed at agriculture in developing countries, but reducing the gender gap and to recommend their roles differ significantly by region practical steps that national governments and are changing rapidly in some areas. and the international community can take Women comprise, on average, 43 percent to promote agricultural development by of the agricultural labour force in empowering women. developing countries, ranging from 20 percent in Latin America to 50 percent in Eastern Asia and sub-Saharan Africa. Structure of the report and key Their contribution to agricultural work messages varies even more widely depending on the specific crop and activity. Chapter 2 provides a survey of the roles • Women in agriculture and rural areas and status of women in agriculture and have one thing in common across rural areas in different parts of the world. regions: they have less access than It brings the best, most comprehensive men to productive resources and available evidence to bear on a number opportunities. The gender gap is found of controversial questions that are both for many assets, inputs and services conceptually and empirically challenging. – land, livestock, labour, education, It focuses on women’s contributions extension and financial services, and as farmers and agricultural workers technology – and it imposes costs on the and examines their status in terms of agriculture sector, the broader economy poverty, hunger and nutrition, and rural and society as well as on women demographics. It also looks at the ways in themselves. which the transformation of agriculture and • Closing the gender gap in agriculture the emergence of high-value marketing would generate significant gains for chains are creating challenges and the agriculture sector and for society. opportunities for women. If women had the same access to Chapter 3 documents the constraints productive resources as men, they facing women in agriculture across a range could increase yields on their farms by of assets: land, livestock, farm labour, 20–30 percent. This could raise total education, extension services, financial agricultural output in developing services and technology. countries by 2.5–4 percent, which could Chapter 4 surveys the economic evidence in turn reduce the number of hungry on the productivity of male and female people in the world by 12–17 percent.
  • 18. 6 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 The potential gains would vary by region resources, education, extension and depending on how many women are financial services, and labour markets; currently engaged in agriculture, how -- investing in labour-saving and much production or land they control, productivity-enhancing technologies and how wide a gender gap they face. and infrastructure to free women’s • Policy interventions can help close the time for more productive activities; gender gap in agriculture and rural labour and markets. Priority areas for reform include: -- facilitating the participation of women -- eliminating discrimination against in flexible, efficient and fair rural women in access to agricultural labour markets.
  • 19. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 7 2. Women’s work Women make essential contributions to participation in the labour force has a agriculture and rural economic activities in positive impact on economic growth (Klasen all developing country regions.1 Their roles and Lamanna, 2009). vary considerably among and within regions and are changing rapidly in many parts of the world where economic and social Women in agriculture forces are transforming the agriculture sector. The emergence of contract farming Women work in agriculture as farmers on and modern supply chains for high-value their own account, as unpaid workers on agricultural products, for example, present family farms and as paid or unpaid labourers different opportunities and challenges on other farms and agricultural enterprises. for women than they do for men. These They are involved in both crop and livestock differences derive from the different roles production at subsistence and commercial and responsibilities of women and the levels. They produce food and cash crops and constraints that they face. manage mixed agricultural operations often Rural women often manage complex involving crops, livestock and fish farming. households and pursue multiple livelihood All of these women are considered part of strategies. Their activities typically include the agricultural labour force.2 producing agricultural crops, tending Based on the latest internationally animals, processing and preparing food, comparable data, women comprise an working for wages in agricultural or other average of 43 percent of the agricultural rural enterprises, collecting fuel and water, labour force of developing countries. The engaging in trade and marketing, caring female share of the agricultural labour for family members and maintaining their force ranges from about 20 percent in Latin homes (see Box 2 for some of the frequently America to almost 50 percent in Eastern and asked questions on the roles and status Southeastern Asia and sub-Saharan Africa of women in agriculture). Many of these (Figure 1). The regional averages in Figure activities are not defined as “economically 1 mask wide variations within and among active employment” in national accounts countries (see Annex tables A3 and A4). but they are all essential to the well-being Women in sub-Saharan Africa have of rural households (see Box 3, page 14, relatively high overall labour-force for a discussion of women’s household participation rates and the highest average responsibilities). agricultural labour-force participation Women often face gender-specific rates in the world. Cultural norms in the challenges to full participation in the region have long encouraged women to be labour force, which may require policy economically self-reliant and traditionally interventions beyond those aimed at give women substantial responsibility for promoting economic growth and the agricultural production in their own right. efficiency of rural labour markets. Policies Regional data for sub-Saharan Africa conceal can influence the economic incentives wide differences among countries. The share and social norms that determine whether of women in the agricultural labour force women work, the types of work they perform and whether it is considered an 2 The agricultural labour force includes people who are economic activity, the stock of human working or looking for work in formal or informal jobs and capital they accumulate and the levels in paid or unpaid employment in agriculture. That includes self-employed women as well as women working on family of pay they receive. Increasing female farms. It does not include domestic chores such as fetching water and firewood, preparing food and caring for children 1 The material in this chapter is based on FAO (2010a). and other family members.
  • 20. 8 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 BOX 2 Frequently asked questions about women in agriculture Question 1: How much of the agricultural Question 3: Do women have less access labour in the developing world is than men to agricultural resources and performed by women? inputs? Answer: Women comprise 43 percent Answer: Yes, this is one generalization of the agricultural labour force, on about women in agriculture that holds average, in developing countries; this true across countries and contexts: figure ranges from around 20 percent in compared with their male counterparts, Latin America to 50 percent in parts of female farmers in all regions control less Africa and Asia, but it exceeds 60 percent land and livestock, make far less use of in only a few countries (FAO, 2010a). improved seed varieties and purchased Critics argue that labour force statistics inputs such as fertilizers, are much less underestimate the contribution of women likely to use credit or insurance, have to agricultural work because women lower education levels and are less likely are less likely to declare themselves as to have access to extension services (see employed in agriculture and they work Chapter 3). longer hours than men (Beneria, 1981), but evidence from time-use surveys does Question 4: Do women and girls comprise not suggest that women perform most of the majority of the world’s poor people? the agricultural labour in the developing Answer: Poverty is normally measured world (see Chapter 2). in terms of income or consumption at the household level, not for individuals, Question 2: What share of the world’s so separate poverty rates for men and food is produced by women? women cannot be calculated. Females Answer: This question cannot be answered could be overrepresented among the in any empirically rigorous way because poor if female-headed households are of conceptual ambiguities and data poorer than male-headed households limitations. Different definitions of “food” (see Question 6) or if significant anti- and “production” would yield different female bias exists within households (see answers to the question and, more Question 7). Females may be poorer than importantly, food production requires males if broader measures of poverty are many resources – land, labour, capital – considered, such as access to productive controlled by men and women who work resources (see Question 3). cooperatively in most developing countries, so separating food production by gender is Question 5: Do women face discrimination not very meaningful (Doss, 2010). in rural labour markets? ranges from 36 percent in Côte d’Ivoire and where the female share of the agricultural the Niger to over 60 percent in Lesotho, labour force has increased slightly since 1980 Mozambique and Sierra Leone. A number of to almost 48 percent. The share of women countries have seen substantial increases in in the agricultural labour force in most the female share of the agricultural labour other countries in the region has remained force in recent decades due to a number fairly steady at between 40 and 50 percent, of reasons, including conflict, HIV/AIDS and although it is substantially lower and migration. declining in some countries such as Malaysia Women in Eastern and Southeastern Asia and the Philippines. also make very substantial contributions to The Southern Asian average is dominated the agricultural labour force, almost as high by India, where the share of women in the on average as in sub-Saharan Africa. The agricultural labour force has remained steady regional average is dominated by China, at just over 30 percent. This masks changes
  • 21. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 9 Answer: In most countries and in keeping Question 7: Are women and girls with global figures, women in rural areas more likely than men and boys to be who work for wages are more likely than undernourished? men to hold seasonal, part-time and low- Answer: A positive answer to this wage jobs and (controlling for education, statement is not supported by available age and industry) women receive lower evidence, and generalizations are difficult wages for the same work (see Chapter 2). to make. The limited evidence available suggests that this may be true in Asia, Question 6: Are female-headed while it is not true in Africa. More sex- households the poorest of the poor? disaggregated data of better quality on Answer: Data from 35 nationally anthropometric and other indicators of representative surveys for 20 countries malnutrition are needed to arrive at clear analysed by FAO show that female- conclusions. There is, however, evidence headed households are more likely to be that girls are much more vulnerable to poor than male-headed households in transitory income shocks than boys (Baird, some countries but the opposite is true Friedman and Schady, 2007). in other countries – so it is not possible to generalize. Data limitations also make it Question 8: Are women more likely than impossible to distinguish systematically men to spend additional income on their between households headed by women children? who are single, widowed or divorced (de Answer: A very large body of research jure female heads) and those who are from many countries around the world associated with an adult male who supports confirms that putting more income in the family through remittances and social the hands of women yields beneficial networks (de facto female heads). It is results for child nutrition, health and likely that the former are more likely to education. Other measures – such as be poor than the latter (Anríquez, 2010). improving education – that increase There is also evidence to suggest that rural women’s influence within the household female-headed households were more are also associated with better outcomes vulnerable than males during the food price for children. Exceptions exist, of course, shock of 2008 because they spend a larger but empowering women is a well-proven proportion of household income on food strategy for improving children’s well- and because they were less able to respond being (see Chapter 4). by increasing food production (Zezza et al., 2008). Again, these results vary by country. in other countries where the female share participation in the region are found in of the agricultural labour force appears to Jordan, the Libyan Arab Jamahiriya and the have increased dramatically, such as Pakistan Syrian Arab Republic. where it has almost tripled since 1980, to The countries of Latin America have high 30 percent, and Bangladesh where women overall female labour-force participation now exceed 50 percent of the agricultural rates, but much lower participation in labour force. agriculture than those in other developing The female share of the agricultural labour country regions. This pattern reflects force in the Near East and North Africa relatively high female education levels appears to have risen substantially, from (see Chapter 4), economic growth and 30 percent in 1980 to almost 45 percent. diversification, and cultural norms that Some of the highest and fastest-growing support female migration to service jobs rates of female agricultural labour force in urban areas. Just over 20 percent of the
  • 22. 10 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 1 Female share of the agricultural labour force Percentage 60 50 40 30 20 10 0 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 Eastern and Southeastern Asia Latin America and the Caribbean Near East and North Africa Southern Asia Sub-Saharan Africa Note: The female share of the agricultural labour force is calculated as the total number of women economically active in agriculture divided by the total population economically active in agriculture. Regional averages are weighted by population. Source: FAO, 2010b. See Annex table A4. agricultural labour force in Latin America Time-use surveys attempt to provide a was female in 2010, slightly higher than complete account of how men and women in 1980. The South American countries of allocate their time.3 Such studies generally the Plurinational State of Bolivia, Brazil, are not nationally representative and are Colombia, Ecuador and Peru dominate both not directly comparable because they usually the average and the rising trend, while cover small samples, report on different many countries in Central America and the types of activities (that are not always clearly Caribbean have seen declining shares of specified) and use different methodologies. women in the agricultural labour force. Despite these caveats, a summary of the Although in some countries sex- evidence from studies that specify time use disaggregated data collection has improved by agricultural activity suggests interesting over recent decades, some researchers patterns. have raised concerns as to the validity of Time-use surveys that cover all agricultural agricultural labour-force statistics as a activities (Figure 2) reveal considerable measure of women’s work in agriculture variation across countries, and sometimes (Beneria, 1981; Deere, 2005). Women’s within countries, but the data are broadly participation in the agricultural labour force similar to the labour force statistics discussed may underestimate the amount of work above. In Africa, estimates of the time women do because women are less likely contribution of women to agricultural than men to define their activities as work, they are less likely to report themselves 3 It is commonly claimed that women perform as being engaged in agriculture and they 60–80 percent of the agricultural labour in developing work, on average, longer hours than men countries (UNECA, 1972; World Bank, FAO and IFAD, 2009). The evidence from time-use surveys and agricultural – so even if fewer women are involved labour-force statistics does not support this general they may contribute more total time to the statement, although women do comprise over 60 percent sector. of the agricultural labour force in some countries.
  • 23. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 11 FIGURE 2 Proportion of labour in all agricultural activities that is supplied by women Gambia United Republic of Tanzania Burkina Faso Nigeria Zambia (1) Zambia (2) Cameroon (Centre–South) Cameroon (Yassa of Campo, Southwest) Cameroon (Mvae of Campo, Southwest) Niger Togo Ghana India/West Bengal India India/Rajasthan Nepal China Peru (1) Peru (2) 0 10 20 30 40 50 60 70 80 Percentage of labour supplied by women Africa Asia Latin America Note: Only the survey for India is nationally representative. Sources (from top to bottom): Gambia: von Braun and Webb, 1989; United Republic of Tanzania: Fontana and Natali, 2008; Burkina Faso: Saito, Mekonnen and Spurling, 1994; Nigeria: Rahji and Falusi, 2005; Zambia (1): Saito, Mekonnen and Spurling, 1994; Zambia (2): Kumar, 1994; Cameroon, Centre–South: Leplaideur, 1978, cited by Charmes, 2006: Cameroon (Yasssa of Campo, Southwest): Charmes, 2006, based on Pasquet and Koppert, 1993 and 1996; Cameroon (Mvae of Campo, Southwest): Charmes, 2006, based on Pasquet and Koppert, 1993 and 1996; Niger: Baanante, Thompson and Acheampong, 1999; Togo: Baanante, Thompson and Acheampong, 1999; Ghana: Baananate, Thompson and Acheampong, 1999; India (West Bengal): Jain, 1996; India: Singh and Sengupta, 2009; India (Rajasthan): Jain, 1996; Nepal: Joshi, 2000; China: de Brauw et al., 2008; Peru (1): Deere, 1982; Peru (2): Jacoby, 1992.
  • 24. 12 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 activities ranges from about 30 percent in is a predominantly female activity, but the Gambia to 60–80 percent in different women are typically involved to some extent parts of Cameroon. In Asia, estimates range in all activities except ploughing. from 32 percent in India to over 50 percent Studies from Indonesia reveal greater in China. The range is lower in Latin America, involvement of women in upland rice but exceeds 30 percent in some parts of Peru. production than that of wet rice and in the A striking degree of within-country variation management of young plantation crops is shown by the study for India. While this such as cinnamon and rubber rather than nationally representative study indicates that the same crops at maturity. As noted above, the national average for women’s share of the data for India hide wide variations total time-use in agriculture is 32 percent, between West Bengal and Rajasthan, but the share ranges from less than 10 percent in both areas, younger women contribute in West Bengal to more than 40 percent in a higher share of the total time provided Rajasthan. in agriculture by their age group than These studies also reveal that female time- older women do in theirs. In Rajasthan, use in agriculture varies widely depending for example, girls aged between 14 and 19 on the crop and the phase of the production contribute up to 60 percent of the total time cycle, the age and ethnic group of the spent on agriculture by their age group (Jain, women in question, the type of activity and 1996). Two separate studies are reported a number of other factors (Figure 3). Planting each for Peru and Zambia, and differences FIGURE 3 Proportion of labour for selected crops that is supplied by women Young rubber Mature rubber Young cinnamon Mature cinnamon Wet rice Upland rice Rice Rice Rice Tomatoes 0 10 20 30 40 50 60 70 80 Percentage of labour supplied by women Indonesia Bangladesh Philippines Viet Nam Dominican Republic Sources (from top to bottom): Indonesia (young rubber): Quisumbing and Otsuka, 2001a; Indonesia (mature rubber): Quisumbing and Otsuka, 2001a; Indonesia (young cinnamon): Quisumbing and Otsuka, 2001a; Indonesia (mature cinnamon): Quisumbing and Otsuka, 2001a; Indonesia (wet rice): Quisumbing and Otsuka, 2001a; Indonesia (upland rice): Quisumbing and Otsuka, 2001a; Bangladesh: Thompson and Sanabria, 2010; Philippines: Estudillo, Quisumbing and Otsuka, 2001; Viet Nam: Paris and Chi, 2005; Dominican Republic: Raynolds, 2002.
  • 25. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 13 reflect different time periods and locations Evidence shows, however, that female within the countries. farmers are largely excluded from modern Time-use studies permit a rich analysis contract-farming arrangements because they of what men and women do in agriculture lack secure control over land, family labour and how their roles may differ by crop, and other resources required to guarantee location, management structure, age and delivery of a reliable flow of produce. For ethnic group. They offer policy-relevant example, women comprise fewer than information about where, when and how 10 percent of the farmers involved in to target interventions aimed at women smallholder contract-farming schemes in and how to bring men into the process the Kenyan fresh fruit and vegetable export constructively. Given the variation in gender sector (Dolan, 2001), and only 1 of a sample roles in agriculture, generalizations about of 59 farmers contracted in Senegal to time use from one region to another are produce French beans for the export sector not appropriate. Studies that consider the was a woman (Maertens and Swinnen, 2009). gender roles within their specific geographic While men control the contracts, however, and cultural context can provide practical much of the farm work done on contracted guidance for policy-makers and practitioners plots is performed by women as family involved in technology investments, labourers. For example, in 70 percent of the extension services, post-harvest activities and cases of sugar contract-farming in South marketing interventions. Africa, the principal farmer on the sugar- One generalization that does hold is cane plots is a woman (Porter and Philips- that women usually allocate time to food Horward, 1997). Women work longer hours preparation, child care and other household than men in vegetable contract-farming responsibilities in addition to the time schemes controlled by male farmers in they spend in agriculture (see Box 3). In the Indian Punjab (Singh, 2003). In a large most societies, household responsibilities contract-farming scheme involving thousands are divided along gender lines, although of farmers in China, women – while excluded these norms differ by culture and over time. from signing contracts themselves – perform Depending on the household structure and the bulk of the work related to contract size, these tasks may be extremely time- farming (Eaton and Shepherd, 2001). Women intensive. Across regions, time allocation may not be well compensated as unpaid studies have shown that women work family labour in contract-farming schemes significantly more than men if care-giving is (Maertens and Swinnen, 2009). included in the calculations (Ilahi, 2000). The Evidence is mixed regarding whether combination of commitments often means contract farming increases overall household that women are more time-constrained than incomes or creates conflicts between the men (Blackden and Wodon, 2006). production of cash crops and food crops. For example, Dolan (2001) argues that the Women in modern contract-farming4 growth of high-value horticulture supply One noteworthy feature of modern chains has been detrimental for rural agricultural value chains is the growth of women in Kenya because land and labour contract farming or out-grower schemes for resources that were traditionally used by high-value produce through which large- women to cultivate vegetables for home scale agroprocessing firms seek to ensure consumption and sale in local markets a steady supply of quality produce. Such have been appropriated by men for export schemes can help small-scale farmers and vegetable production under contract. On livestock producers overcome the technical the other hand, although their results are barriers and transaction costs involved in not gender-specific, Minten, Randrianarison meeting the increasingly stringent demands and Swinnen (2009), find that high-value of urban consumers in domestic and vegetable contract-farming in Madagascar international markets. leads to improved productivity for food (rice) production through technology spillovers, 4 The material in this section is based on Maertens and thereby improving the availability of food Swinnen (2009). in the household and shortening the lean
  • 26. 14 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 BOX 3 Women and unpaid household responsibilities Women have primary responsibilities for Because of the gender-specific household and child-rearing activities assignment of tasks, any change affecting in most societies, although norms differ the family or the environment may by culture and are changing over time. have different implications for men and Time-use surveys across a wide range of women. HIV/AIDS, for example, has caused countries estimate that women provide a significant increase in the time needed 85–90 percent of the time spent on to care for sick family members or the household food preparation and that orphaned children of relatives (Addati they are also usually responsible for child and Cassirer, 2008). Deforestation leads care and other household chores. The women to travel increasing distances from combined time burden of household the homestead to collect firewood (Kumar chores and farm work is particularly severe and Hotchkiss, 1988; Nankhuni, 2004). for women in Africa (Ilahi, 2000). Poor infrastructure and limited provision Ghanaian women carry a much heavier of public services require Tanzanian burden for household chores despite women in rural areas to spend long working outside the home almost as much hours on water and fuel collection, food as men (Brown, 1994). In Uganda, women preparation and other domestic and cite the time they spend looking after child-care activities. Improving public their families, working in their husbands’ infrastructure for water and fuel collection gardens and producing food for their and food preparation (e.g. grain-milling households as reasons for their inability to facilities) could free women in the United expand production for the market (Ellis, Republic of Tanzania from a burden that Manuel and Blackden, 2006). Women and represents 8 billion hours of unpaid work girls in Ghana, the United Republic of per year, which is equivalent to the hours Tanzania and Zambia are responsible for required for 4.6 million full-time jobs. The about 65 percent of all transport activities same improvements would save time for in rural households, such as collecting men also, but less: the time-equivalent of firewood and water and carrying grain to 200 000 full-time jobs (Fontana and Natali, the grinding mill (Malmberg-Calvo, 1994). 2008). period or “hunger season”. Maertens and engaged in the sector. An estimated two- Swinnen (2009) do not find evidence of thirds of poor livestock keepers, totalling gender conflict over resources in the French approximately 400 million people, are bean export sector in Senegal because women (Thornton et al., 2002). They share households only allocate part of their land responsibility with men and children for the and labour resources to bean production, care of animals, and particular species and which occurs during the off-season and does types of activity are more associated with not coincide with the main rainy season women than men. For example, women when staple food crops and other subsistence often have a prominent role in managing crops are cultivated. poultry (FAO, 1998; Guèye, 2000; Tung, 2005) and dairy animals (Okali and Mims, Women as livestock keepers5 1998; Tangka, Jabbar and Shapiro, 2000) Within pastoralist and mixed farming and in caring for other animals that are systems, livestock play an important role in housed and fed within the homestead. supporting women and in improving their When tasks are divided, men are more financial situation, and women are heavily likely to be involved in constructing housing and the herding of grazing animals, and in marketing products if women’s mobility 5 The material in this section was prepared by FAO’s Agriculture and Consumer Protection Department, Animal is constrained. The influence of women is Production and Health Division. strong in the use of eggs, milk and poultry
  • 27. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 15 meat for home consumption and they out of business. This is particularly evident often have control over marketing these for pig and poultry owners (Rola et al., 2006) products and the income derived from but is not confined to those species. Given them. Perhaps for this reason, poultry and the more limited ability of women to start small-scale dairy projects have been popular their own businesses, this implies that they investments for development projects that will tend to become employees rather than aim to improve the lot of rural women. In self-employed. In specialized activities such some countries, small-scale pig production is as the production of day-old chicks, and in also dominated by women. Female-headed slaughtering, processing and retail, women households are as successful as male-headed are visible wherever painstaking semi-skilled households in generating income from their work is to be done, but very little research animals, although they tend to own smaller data are available about the extent of their numbers of animals, probably because of involvement compared with that of men, or labour constraints. Livestock ownership is their control over resources. particularly attractive to women in societies where access to land is restricted to men Women in fisheries and aquaculture6 (Bravo-Baumann, 2000). In 2008, nearly 45 million people worldwide While the role of women in small-scale were directly engaged, full time or part time, livestock production is well recognized, much in the fishery primary sector.7 In addition, an less has been documented about women’s estimated 135 million people are employed engagement in intensive production and in the secondary sector, including post- the market chains associated with large harvest activities. While comprehensive data commercial enterprises. Demand for livestock are not available on a sex-disaggregated products, fuelled by rising incomes, has basis, case studies suggest that women grown much faster than the demand for crop may comprise up to 30 percent of the total staples during the past 40 years – particularly employment in fisheries, including primary in Asia and Latin America – and this trend is and secondary activities. expected to continue. While pastoralist and Information provided to FAO from 86 small-scale mixed-farming systems continue countries indicates that in 2008, 5.4 million to be important in meeting the needs of women worked as fishers and fish farmers rural consumers, the demands of growing in the primary sector. This represents urban populations are increasingly supplied 12 percent of the total. In two major with meat, milk and eggs from intensive producing countries, China and India, commercial systems. This has implications women represented a share of 21 percent for the engagement of women in the and 24 percent, respectively, of all fishers and livestock sector because of the different fish farmers. roles, responsibilities and access to resources Women have rarely engaged in commercial that are evident within different scales of offshore and long-distance capture production system and at different points on fisheries because of the vigorous work the production and marketing chain. involved but also because of their domestic The available evidence suggests that the responsibilities and/or social norms. They role of women in meeting these changing are more commonly occupied in subsistence demands may diminish, for two reasons. and commercial fishing from small boats and The first is that when livestock enterprises canoes in coastal or inland waters. Women scale up, the control over decisions and also contribute as entrepreneurs and provide income, and sometimes the entire enterprise, labour before, during and after the catch often shifts to men. This is not a universal in both artisanal and commercial fisheries. phenomenon – in Viet Nam, for example, For example, in West Africa, the so called many medium-sized duck-breeding “Fish Mamas” play a major role: they usually enterprises are managed by women – but it is common and can be explained by women’s 6 The material in this section was prepared by FAO’s limited access to land and credit. The second Fisheries and Aquaculture Department. 7 FAO’s Fisheries and Aquaculture Department regularly important factor is that all smallholders collects employment statistics in fisheries and aquaculture face challenges when the livestock sector related to the primary sector only. The data therefore intensifies and concentrates and many go exclude post-harvest activities.
  • 28. 16 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 own capital and are directly and vigorously IFAD, 2009). Studies conducted by FAO in involved in the coordination of the fisheries Africa and Europe indicate that women do chain, from production to the sale of fish. not hold senior or policy-making positions Studies of women in aquaculture, in the sector. Rather, they are primarily especially in Asia where aquaculture employed in administrative and support has a long tradition, indicate that the roles, with professional women foresters contribution of women in labour is often tending to have specialist roles (e.g. research) greater than men’s, although macro-level or first-line junior management positions. sex-disaggregated data on this topic is There is limited information on the numbers almost non-existent. Women are reported and roles of women in contracting or self- to constitute 33 percent of the rural employed forestry work (FAO, 2006a, 2007). aquaculture workforce in China, 42 percent The studies indicate that even though women in Indonesia and 80 percent in Viet Nam are still underrepresented in the industry, (Kusabe and Kelker, 2001). examples of good practice are emerging, The most significant role played by women especially in Europe (FAO, 2006a). This shows in both artisanal and industrial fisheries is that concerted and sustained commitment at the processing and marketing stages, and planning at senior organizational levels where they are very active in all regions. can result in quantifiable improvements in In some countries, women have become the number of professional women foresters significant entrepreneurs in fish processing; employed and the level of seniority they can in fact, most fish processing is performed by attain. women, either in their own household-level industries or as wage labourers in the large- scale processing industry. Women in rural labour markets Women in forestry About 70 percent of men and 40 percent Women contribute to both the formal and of women in developing countries are informal forestry sectors in many significant employed (Figure 4A). Male employment ways. They play roles in agroforestry, rates range from more than 60 percent in watershed management, tree improvement, the Near East and North Africa to almost and forest protection and conservation. 80 percent in sub-Saharan African. Female Forests also often represent an important employment rates vary more widely across source of employment for women, especially regions, from about 15 percent in the Near in rural areas. From nurseries to plantations, East and North Africa to over 60 percent in and from logging to wood processing, sub-Saharan Africa. women make up a notable proportion of the In Asia and in sub-Saharan Africa, women labour force in forest industries throughout who are employed are more likely to be the world. However, although women employed in agriculture than in other contribute substantially to the forestry sectors (Figure 4B). Almost 70 percent of sector, their roles are not fully recognized employed women in Southern Asia and and documented, their wages are not more than 60 percent of employed women equal to those of men and their working in sub-Saharan Africa work in agriculture. conditions tend to be poor (World Bank, FAO Furthermore, in most developing country and IFAD, 2009). regions, women who are employed are just The Global Forest Resources Assessment as likely, or even more likely, than men to 2010 reports that the forestry sector be in agriculture. The major exception is worldwide employed approximately Latin America, where agriculture provides a 11 million people in 2005; however, sex- relatively small source of female employment disaggregated data on the number of and women are less likely than men to work women employed by the sector are not in the sector. available on a comprehensive basis (FAO, In most developing countries, a relatively 2010c). Evidence from developing countries small share of the population works for a suggests that women are often employed in wage, and women are less likely to do so menial jobs in sawmills, plantation nurseries than men (World Bank, 2007a). For rural and logging camps (World Bank, FAO and areas, data collected by the Rural Income
  • 29. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 17 FIGURE 4 Employment by sector A - Employed population as a share of total adult population, by sex and sector Percentage of total male and female population, respectively 80 70 60 50 40 30 20 10 0 Males Females Males Females Males Females Males Females Males Females Males Females Developing Eastern and Latin America Near East and Southern Asia Sub-Saharan countries Southeastern and the North Africa Africa Asia Caribbean B - Distribution of male and female employment, by sector Percentage of male and female employment, respectively 100 90 80 70 60 50 40 30 20 10 0 Males Females Males Females Males Females Males Females Males Females Males Females Developing Eastern and Latin America Near East and Southern Asia Sub-Saharan countries Southeastern and the North Africa Africa Asia Caribbean Agriculture Industry Services Note: The data cover only a subset of the countries in each region. Definitions of adult labour force differ by country, but usually refer to the population aged 15 and above. Source: ILO, 2009. Generating Activities (RIGA) project show For example, almost 15 percent of men that the gender gap in formal and informal but fewer than 4 percent of women are wage employment is large (Figure 5).8 employed for wages in Ghana. The gap is even wider in some other countries, such as 8 Rural Income Generating Activities (RIGA) is a FAO project Bangladesh, where 24 percent of rural men that has created an internationally comparable database of and only 3 percent of rural women work in rural household income sources from existing household living wage employment. A similar pattern holds in standards surveys for more than 27 countries (FAO, 2010d). Latin America also; for example, in Ecuador Most of the surveys used by the RIGA project were developed by national statistical offices in conjunction the World Bank as almost 30 percent of rural men and only part of its Living Standards Measurement Study (LSMS). 9 percent of rural women receive a wage.
  • 30. 18 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 5 Participation in rural wage employment, by gender Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Tajikistan Viet Nam Ghana Malawi Nigeria 0 5 10 15 20 25 30 35 Percentage of adult population working for a wage Women Men Source: FAO, 2010d. Even when rural women are in wage Differences in male and female employment, they are more likely to be employment and wage patterns may have in part-time, seasonal and/or low-paying multiple causes. Because women in many jobs. In Malawi, for example, 90 percent of countries have less education and work women and 66 percent of men work part- experience than men, they may earn a lower time (Figure 6A). In Nepal, 70 percent of wage. Furthermore, having less education women and 45 percent of men work part- and experience reduces their bargaining time. This pattern is less pronounced in Latin power so they may be more likely to accept America than in other regions. low wages and irregular working conditions Rural wage employment is characterized (Kantor, 2008). Evidence from a number of by a high prevalence of seasonal jobs studies confirms that women, on average, for both men and women, but in most are paid less than men even for equivalent countries women are more likely than men jobs and comparable levels of education to be employed seasonally (Figure 6B). For and experience (Ahmed and Maitra, 2010; example, in Ecuador, almost 50 percent of Fontana, 2009). At the same time, because women but fewer than 40 percent of men women face significant time constraints hold seasonal jobs. because of family obligations, they may prefer Similarly, rural wage-earning women are part-time or seasonal jobs that are typically more likely than men to hold low-wage jobs lower paid. Social norms that confine women (Figure 6C), defined as paying less than the to certain sectors or phases of the supply median agricultural wage. In Malawi, more chain can further limit their opportunities for than 60 percent of women are in low-wage career growth and reinforce these sectors as jobs compared with fewer than 40 percent low-pay and low-status occupations. of men. The gap is even wider in Bangladesh, Average male wages are higher than where 80 percent of women and 40 percent of average female wages in rural and urban men have low-wage jobs. The only exception areas of the countries covered by the to this pattern was found in Panama. RIGA dataset (Figure 7). For example, in
  • 31. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 19 FIGURE 6 Conditions of employment in rural wage employment, by gender A - Prevalence of part-time work Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Tajikistan Viet Nam Ghana Malawi Nigeria 0 10 20 30 40 50 60 70 80 90 100 Percentage B - Prevalence of seasonal work1 Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Tajikistan Viet Nam Malawi 0 10 20 30 40 50 60 70 80 90 100 Percentage C - Prevalence of low-wage work Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Tajikistan Viet Nam Ghana Malawi Nigeria 0 10 20 30 40 50 60 70 80 90 100 Percentage Women Men 1 Data are not available for Ghana and Nigeria. Source: FAO, 2010d.
  • 32. 20 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 Ghana, men’s wages are 31 percent higher developments for female employment over than women’s wages in urban areas and the past few decades (Deere, 2005). 58 percent higher in rural areas. Women earn Women are clearly an important part less than men everywhere except in rural of the agricultural labour force, but areas of Panama. The gap between male and agriculture and agricultural value chains female wages is wider in rural areas in some are equally important to women as a countries, but not everywhere. Women in source of employment. Commercial value most RIGA countries typically earn less than chains for high-value products such as fresh men with the same qualifications, partly as fruit, vegetables, flowers and livestock a consequence of occupational segregation products are growing rapidly to supply and discrimination (Hertz et al., 2009). urban supermarkets and export markets. While women continue to face The growth of modern value chains and occupational segregation and discrimination the broader structural transformation of in rural labour markets, new forms of the agriculture sector in many developing organization in supply chains for export- countries have major implications for oriented crops and agroprocessing have women’s employment, but the impact created better-paying employment of these trends for women has received opportunities for women than had existed relatively little analytical attention (Maertens before. Wages are typically higher and and Swinnen, 2009). working conditions better than in traditional Women dominate employment in many agricultural employment. The large-scale of the high-value agricultural commodity incorporation of women in the packing stage chains in Africa and Latin America (Table 1). of non-traditional agro-export production Although new jobs in export-oriented agro- may be one of the most important industries may not employ men and women FIGURE 7 Wage gap between men and women in urban and rural areas Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Tajikistan Viet Nam Ghana Malawi Nigeria -20 -10 0 10 20 30 40 50 60 70 Percentage Rural Urban Note: The wage gap is calculated as the difference between average daily male and female wages as a percentage of the average male wage. A positive wage gap means men are paid more than women. The rural wage gap includes farm and non-farm employment. Source: Hertz et al. 2009.
  • 33. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 21 TABLE 1 Employment in selected high-value agro-industries Year of Number of employees Share of female Country Commodity survey in the agro-industry employees (%) Cameroon Banana 2003 10 000 .. Côte d’lvoire Banana and pineapple 2002 35 000 .. Kenya Flowers 2002 40 000–70 000 75 French beans 2005 12 000 90 Senegal Cherry tomatoes 2006 3 000 60 Uganda Flowers 1998 3 300 75 South Africa Deciduous fruit 1994 283 000 53 Vegetables 2002/3 7 500 65 Zambia Flowers 2002/3 2 500 35 Chile Fruits 1990s 300 000 circa 46 Colombia Flowers mid-90s 75 000 60–80 Fruits, vegetables, Dominican Republic flowers, plants 1989–90 16 955 circa 41 Mexico Vegetables 1990s 950 000 90 Sources: For Africa: Maertens and Swinnen, 2009, Table 1, based on several sources; for South America: Deere, 2005, Appendix II, based on several sources. on equal terms, they often provide better in some surprising ways (Newman, 2002). The opportunities for women than exist within total time spent by women in paid and unpaid the confines of traditional agriculture and work did not increase, contrary to a frequent can also be instruments of change with criticism of agricultural export development positive implications for women and rural that maintains that women are unduly development (Maertens and Swinnen, 2009; burdened by work in the industry. Indeed, the Deere, 2005). most compelling evidence of the industry’s The flower industry in Latin America impact was on men’s increased participation in provides an interesting case of contrasting housework. In Cotocachi, Ecuador, in contrast, points of view. In Colombia, for example, women were not prepared to move or even Friedemann-Sanchez (2006) finds that commute to work in the flower industry 64 percent of the workforce directly growing despite the higher wages offered there. fresh-cut flowers for export are women and The women did not view flower industry considers this type of agro-industrial work employment as an option, indicating either skilled, while others consider it unskilled that their husbands would not allow them to (e.g. Meier, 1999). While women do have work or that the work would be detrimental supervisory jobs among those directly to family relations (Newman, 2002). involved in cultivation activities, they In Senegal, the growth of modern have a much lower share of managerial or horticulture supply chains has been professional jobs in other aspects of the associated with direct beneficial effects sector (Friedemann-Sanchez, 2006). Similarly, for rural women and reduced gender Fontana (2003) finds that in sectors producing inequalities in rural areas (Maertens and primarily for the export market, women tend Swinnen, 2009). The study also finds that to be replaced by males as profits increase. women benefit more from employment The arrival of the flower industry in the in large-scale estate production and agro- Ecuadorian town of Cayambe in the late 1980s industrial processing than from high-value (in combination with other household and smallholder contract-farming in which they individual factors) affected time-use patterns often provide unpaid family labour.
  • 34. 22 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 • Agriculture is the most important source Key messages of employment for women in rural areas in most developing country regions, but • Women comprise 43 percent of the this varies widely by region. Women are agricultural labour force in developing more likely than men to hold low-wage, countries, on average, ranging from part-time, seasonal employment and about 20 percent in Latin America they tend to be paid less even when their to almost 50 percent in Eastern and qualifications are higher than men’s, but Southeastern Asia and sub-Saharan new jobs in high-value, export-oriented Africa. The share is higher in some agro-industries offer much better countries and is changing rapidly in some opportunities for women than traditional parts of the world. agricultural work.
  • 35. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 23 3. Documenting the gender gap in agriculture9 Access to productive resources such as land, less likely to own or operate land; they are modern inputs, technology, education and less likely to have access to rented land, and financial services is a critical determinant the land they do have access to is often of of agricultural productivity. Agriculture poorer quality and in smaller plots. is important to women, but female The most comprehensive data on women’s farmers (Box 4) have less access to the access to land come from the FAO Gender productive resources and services required and Land Rights Database (FAO, 2010f), and by agricultural producers. Women are less were collected from different data sources, likely than men to own land or livestock, including household surveys, agricultural adopt new technologies, use credit or other censuses and the academic literature. The financial services, or receive education or database provides information on the shares extension advice. In some cases, women do of “agricultural holders” who are male and not even control the use of their own time. female. An agricultural holder is defined as While the size of the gender gap differs the person or group of persons who exercise by resource and location, the underlying management control over an agricultural causes for the gender asset gap are repeated holding. The holding may be owned, across regions: social norms systematically rented or allocated from common property limit the options available to women. resources and may be operated on a share- Regardless of cause or magnitude, however, cropped basis. the gender asset gap reduces the agricultural Stark gender disparities in land holdings productivity of women and thus involves are apparent in all regions (Figure 8). broader economic and social costs. Women represent fewer than 5 percent of all agricultural holders in the countries in North Africa and West Asia for which Land data are available. The sub-Saharan African average of 15 percent masks wide variations, Land is the most important household asset from fewer than 5 percent in Mali to over for households that depend on agriculture 30 percent in countries such as Botswana, for their livelihoods. Access to land is a basic Cape Verde and Malawi. Latin America requirement for farming and control over has the highest regional average share of land is synonymous with wealth, status female agricultural holders, which exceeds and power in many areas. Strengthening 25 percent in Chile, Ecuador and Panama. women’s access to, and control over, land In addition to being more likely to hold is an important means of raising their land, men also typically control larger land status and influence within households and holdings than women. Representative and communities. Improving women’s access comparable data for 20 countries from the to land and security of tenure has direct RIGA database of household surveys show impacts on farm productivity, and can also that male-headed households operate larger have far-reaching implications for improving agricultural land holdings, on average, than household welfare. Strengthening land female-headed households in all countries ownership by women in Nepal, for example, (Figure 9). Inequality in access to land is more is linked with better health outcomes for acute in Bangladesh, Ecuador and Pakistan, children (Allendorf, 2007). where average land holdings of male-headed The evidence illustrating gender inequalities households are more than twice the size of in access to land is overwhelming. Women across all developing regions are consistently 9 The material in this chapter is based on FAO (2010e).
  • 36. 24 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 BOX 4 Female farmers, household heads and data limitations Data on female farmers are limited. Most A distinction should be made between women engaged in farming do so within two types of female-headed households: a household production unit, and their (i) de facto, i.e. those in which an adult activities are not usually separable from male partner is working away from the those of the household as a whole. Most of household but remains involved through the data available on female farmers derives remittances and other economic and from household surveys and pertains to the social ties and (ii) de jure, i.e. those which activities of female-headed households, who have no male partner, such as women comprise a minority of female farmers in who are widowed, divorced or never most countries. Some data are available for married. Comprehensive data are not female-operated plots within male-headed usually available to distinguish between households, primarily in Africa where men these types of households, but for the and women often operate separate plots. few cases for which we have data most The unit of observation used in this chapter female-headed households are de jure. (individuals, households, farms or plots) In Malawi, Panama and Uganda about varies depending on the resource being 70, 63 and 83 percent, respectively, of discussed and the availability of data. all female-headed households are de The prevalence of female-headed jure (Chipande, 1987; Appleton, 1996; households is generally higher in sub- and Fuwa, 2000). Also in Cambodia and Saharan Africa than in other regions the Lao People’s Democratic Republic, (Annex table A5), but this hides most are de jure (FAO/GSO/MoP, 2010, considerable variation within the region. and FAO/MAF, 2010). Studies that are In fact, the countries having the highest able to disaggregate by type of female- (Swaziland) and the lowest (Burkina Faso) headed household mostly find that de prevalence of female-headed households jure households are more likely to suffer in developing regions are both found in from a range of economic and social sub-Saharan Africa. disadvantages (Seebens, 2010). those of female-headed households. The to systematic gender inequalities. Male- RIGA results confirm the findings of studies headed households have larger livestock in Latin America (Deere and León, 2003) holdings, on average, than female-headed and Africa (FAO, 1997) showing that male- households (Figure 10). Inequality in livestock controlled land holdings are generally larger holdings appears to be particularly acute in than female-controlled holdings. Bangladesh, Ghana and Nigeria, where male holdings are more than three times larger than those of female-headed households. In Livestock Indonesia and Pakistan, for which the RIGA database contains information on incomes Livestock is another key asset in rural areas from livestock but not livestock holdings, (FAO, 2009a). In many countries, livestock net incomes from livestock are significantly is one of the most valuable agricultural higher in male-headed households than in assets and represents a source of income female-headed households. and wealth accumulation as well as an The RIGA database provides information important source of resistance to shocks. by household according to the sex of the Draught animals are also the main source household head, so data do not reflect of power for ploughing, land clearing and intra-household differences in control over transportation in many regions. livestock. These vary by culture and context As was the case for access to land, the but, in general, men are responsible for evidence for livestock holdings points keeping and marketing large animals, such
  • 37. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 25 FIGURE 8 Share of male and female agricultural holders in main developing regions Latin America and the Caribbean Sub-Saharan Africa Southern Asia and Southeastern Asia North Africa and West Asia Oceania 0 10 20 30 40 50 60 70 80 90 100 Percentage Female Male Note: Regional aggregates do not include all countries due to lack of data. Country-level data are provided in Annex table A5. Source: FAO, 2010f. FIGURE 9 Rural household assets: farm size Bolivia Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Pakistan Tajikistan Viet Nam Ghana Madagascar Malawi 0 1 2 3 4 5 6 7 8 9 10 11 Average farm size (ha) Female-headed households Male-headed households Note: Differences between male and female-headed households are statistically significant at the 95 percent confidence level for all countries, except for Bolivia, Indonesia, Madagascar, Nicaragua and Tajikistan. Sources: FAO, 2010d, and Anríquez, 2010.
  • 38. 26 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 10 Household livestock assets, in male- and female-headed households Bolivia Ecuador Guatemala Nicaragua Panama Bangladesh Nepal Ghana Madagascar Malawi Nigeria 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 Average tropical livestock unit (TLU) Female-headed households Male-headed households Notes: Calculations made using nationally representative household surveys. The number of livestock is computed using the tropical livestock unit (TLU), which is equivalent to a 250 kg animal. The scale varies by region. For example, in South America, the scale is: 1 bovine = 0.7 TLU, 1 pig = 0.2, 1 sheep = 0.1 and 1 chicken = 0.01. Differences between male- and female-headed households are statistically significant at the 95 percent confidence level for all countries except for Guatemala. Sources: FAO, RIGA team, and Anríquez, 2010. as cattle, horses and camels, while women the form of large animals such as cows and tend to control smaller animals, such as bulls while women are more likely to hold goats, sheep, pigs and poultry (FAO, 2009a). assets in the form of small animals, household In Nicaragua, for example, women own durable goods and jewellery. Women tend around 10 percent of work animals and to draw down assets more quickly than men cattle but 55–65 percent of pigs and poultry in response to crises and as they get older (Deere, Alvarado and Twyman, 2009). Even (Dillon and Quiñones, 2010). when women jointly own large animals, they do not necessarily have access to the services they provide, as was found for Indian women Farm labour and the use of oxen (Chen, 2000). The RIGA data measure livestock in physical Labour availability depends on the amount terms – tropical livestock units – but the of family labour that a household can results are consistent with other studies that mobilize and the amount of labour that can evaluate the value of livestock holdings. Data be hired in local labour markets. Labour from northern Nigeria, for example, indicate constraints can be more acute for both that the value of men’s livestock holdings women and female-headed households is about twice that of women’s (Dillon and than for men and male-headed households Quiñones, 2010). The same study finds that for several reasons. Women generally face men and women use livestock differently gender-specific constraints as agricultural as a store of wealth and as a buffer against labourers and in hiring-in labour. Low levels shocks. Men are more likely to hold assets in of human capital – education, health and
  • 39. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 27 nutrition – are a constraint on women’s that female-headed households typically labour productivity in agriculture and other farm smaller plots may not compensate for sectors (Behrman, Alderman and Hoddinott, the lower availability of family labour. For 2004) (Box 5). Some nutrition issues, such example, among small-scale maize farmers as iron deficiency, which directly affects in Malawi, females own less land but still labour productivity and is widespread, are use about 10 percent less total labour per especially relevant to women (Quisumbing hectare than their male counterparts and and Pandolfelli, 2010). Often there is a much of that labour is supplied by children, pronounced gender division of labour for who must work to make up the shortfall particular agricultural tasks, with the result caused by their mothers’ other duties that male and female labour cannot be easily (Takane, 2008). substituted. Moreover, women are time- Household and community responsibilities constrained by domestic tasks such as care- and gender-specific labour requirements giving and collecting firewood and water mean that women farmers cannot farm (McGuire and Popkin, 1970; Quisumbing and as productively as men and make it more Pandolfelli, 2010). difficult for them to respond when crop Female-headed households face more prices rise. Depending on cultural norms, severe labour constraints than male-headed some farming activities, such as ploughing households because they typically have and spraying, rely on access to male labour fewer members but more dependants. In without which women farmers face delays some areas, male out-migration adds to that may lead to losses in output. For the constraint already imposed by gender- example, women maize farmers in Malawi specific farming tasks (Peters, 1986). Female- require male labour for ploughing, but headed households may receive help from female-headed households often lack male male relatives, but only after the men have family members who can do the work and taken care of their own plots. The fact they may not have the cash needed to hire BOX 5 Labour productivity and hunger, nutrition and health Hunger, nutrition and health are strong whereas the opposite is true in sub- determining factors on a person’s ability Saharan Africa. to work, their productivity and their While in some locations women are cognitive development. With regard to disadvantaged with regard to hunger and nutrition, only 37 developing countries nutrition, this is not generally the case. collect data on chronic energy deficiency However, there are certain health and (CED) for both men and women (Annex nutritional issues that are sex-specific. For table A6) (WHO, 2010). In 17 countries the example, women’s energy and nutritional difference between the share of men and needs increase during menstruation, women with CED is one or less percentage pregnancy and lactation and their points. Of the remaining 20 countries, nutritional status has an impact on their 13 show a higher share of women with offspring. There is also evidence that women CED. Based on these few observations, have higher morbidity than men – not only it appears that in sub-Saharan Africa because they live longer – and that they are women are less likely than men to suffer less likely to access health services (Buvinic CED while in South America and Asia, et al., 2006). Thus, gender differences in particularly Southeastern Asia, women are nutrition and health could have important more likely than men to suffer from CED. policy implications for society. The reported data for adults are consistent Policy interventions that address the with that available for underweight specific health and nutrition issues of children (under 5 years of age). For women are important, but their nature example, in Asia and the Pacific, a larger and scope should always reflect the share of girls than boys are underweight, specific context and location.
  • 40. 28 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 male labour. As a result, women cultivate The level of human capital available in smaller plots and achieve lower yields a household (usually measured as the (Gilbert, Sakala and Benson, 2002). This web education of the head of household or the of constraints means that women in Malawi average education of working-age adults in have difficulty growing cash crops such as the household) is strongly correlated with tobacco or improved maize that require measures such as agricultural productivity, purchased inputs, because they cannot household income and nutritional outcomes generate the income necessary to obtain – all of which ultimately affect household credit and guarantee repayment. Such labour welfare and economic growth at the national constraints in some cases may prevent female- level (World Bank, 2007a). headed households from even applying for Gender differences in education are credit (Chipande, 1987). Female-headed significant and widespread (Figure 11). households in Ethiopia, where cultural norms Female heads have less education than require that ploughing be undertaken by their male counterparts in all countries men, also achieve lower yields because they in the sample except Panama, where the have limited access to male labour (Holden, difference is not statistically significant. The Shiferaw and Pender, 2001). data suggest that female household heads in rural areas are disadvantaged with respect to human capital accumulation in most Education developing countries, regardless of region or level of economic development. Human capital is a major factor in This evidence reflects a history of bias determining the opportunities available to against girls in education. Despite this bias, individuals in society and is closely linked human capital accumulation is one asset to the productive capacity of households category for which the gender gap has and their economic and social well-being. clearly narrowed in recent decades. Although FIGURE 11 Education of male and female rural household heads Bolivia Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Pakistan Tajikistan Viet Nam Ghana Madagascar Malawi Nigeria 0 1 2 3 4 5 6 7 8 9 10 11 Average years of education of household head Female-headed households Male-headed households Sources: FAO, 2010d, and Anríquez, 2010.
  • 41. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 29 FIGURE 12 Gender differences in rural primary education attendance rates Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Pakistan Viet Nam Ghana Madagascar Malawi Nigeria 0 10 20 30 40 50 60 70 80 90 100 Net primary attendance rates (percentage) Female Male Note: Attendance rates are defined as the number of children in primary school age who attend primary school, expressed as a percentage of the total number of children in official primary school age. Only Ghana, Guatemala, Nepal and Pakistan are statistically significantly different from 0 at the 95 percent level. Source: FAO, RIGA team. progress has been uneven across regions science and technology is particularly and important gaps persist, significant gains relevant in regions where women comprise have been made in primary school enrolment a large part of the agriculture sector. The rates for girls, and difference between boys number of women working in science and girls has narrowed. Of the 106 countries and technology research in industrialized committed to MDG 3 on gender parity in and developing countries has increased access to education, 83 had met the target substantially in recent decades, but remains by 2005 (World Bank, 2007b). Most of the low in most countries. There is an urgent countries in the RIGA database have achieved need for a greater representation of women gender parity in primary school attendance in agricultural research, particularly in sub- (defined as no statistically significant Saharan Africa, where women participate difference between male and female heavily in the agricultural workforce. Women attendance rates) (Figure 12). One of the scientists, research managers, lecturers and most significant advances for women in Latin professors can provide different insights America has been in the area of primary and perspectives and help research agencies and secondary education, yet a significant to address more effectively the unique and gender gap persists among indigenous pressing challenges that African farmers groups in many Latin American countries. face. They may also serve as role models to The education gender gap – both in levels of students and other women in agriculture. enrolment and attainment – remains widest Significant progress has been made in in Southern Asia and sub-Saharan Africa. increasing the share of female professional Beyond general educational attainment, staff in agricultural higher education and higher education for women in agricultural research institutions in Africa (Box 6).
  • 42. 30 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 BOX 6 Women in agricultural higher education and research in Africa1 During 2008, the Agricultural Science the Niger (10 percent) and Burkina Faso and Technology Indicators (ASTI) and the (12 percent). Compared with other African Woman in Agricultural Research countries in the region, female professional and Development (AWARD) programmes staff members were relatively more conducted a survey to obtain sex- educated in Kenya, Nigeria, South Africa disaggregated capacity indicators covering and Uganda, where more than one-quarter 125 agricultural research and higher of the total held PhD degrees. education agencies in 15 sub-Saharan Future trends in female participation in African countries.2 The study found that the agricultural research will be influenced by pool of female professional staff increased current student enrolment and graduation by 50 percent between 2000/01 and levels. An increasing number of women 2007/08 and 4 (Botswana, Nigeria, Senegal, have been enrolling in higher education, and Zambia) of the 15 countries saw their not only in sub-Saharan Africa, but also female staff double. In relative terms, the in other regions in the world (UIS, 2006; share of women in total professional staff UNESCO, 2004). This also appears to increased from 18 percent to 24 percent be the case in agricultural sciences, but over the period. This increase occurred unfortunately no sex-disaggregated trend across all three degree levels (BSc, MSc, data are available. Most female students and PhD), but varied considerably across in agricultural sciences, however, are the 15 countries (Figures A and B). Female enrolled in BSc programmes. This is also participation in agricultural research and true for male students and reflects the higher education was particularly high in reality that many agricultural faculties and South Africa (41 percent), Mozambique schools in sub-Saharan Africa have only (35 percent) and Botswana (32 percent). small MSc and PhD programmes. In contrast, only a small proportion of the The growing shares of professional agricultural professional staff were women women employed in agriculture and in Ethiopia (6 percent), Togo (9 percent), female students enrolled in agricultural FIGURE A Change in average female shares in professional staff of agricultural and higher education institutions in 14 African countries, by degree level, 2000/01 to 2007/08 Percentage 30 25 20 15 10 5 0 BSc MSc PhD Total Degree level 2000/01 2007/08 Note: Excludes Mozambique owing to lack of available data for 2000/01. Source: Beintema and Di Marcantonio, 2009, based on ASTI datasets.
  • 43. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 31 FIGURE B Change in female shares in professional staff, by headcount, 2000/01 to 2007/08 Botswana Burkina Faso Burundi Ethiopia Ghana Kenya Malawi Mozambique Niger Nigeria Senegal South Africa Togo Uganda Zambia Total (15) Total (14) 0 5 10 15 20 25 30 35 40 45 Percentage 2000/01 2007/08 Note: Excludes Mozambique owing to lack of available data for 2000/01. Source: Beintema and Di Marcantonio, 2009, based on ASTI datasets. sciences indicate that the gender gap ladder. Only 14 percent of management in African agricultural sciences may positions were held by women, which is be narrowing, especially in southern considerably lower than the overall share Africa. But the increase in the number of of female professional staff employed women, as well as men, that enter African in agriculture. Women are, therefore, agricultural research and higher education less represented in high-level research, are mostly young staff with lower level management and decision-making of degrees and at the beginning of the positions compared with their male career ladder. On average, more than colleagues. half of the female professional staff in the 15-country sample were younger 1 This section was prepared by Nienke Beintema than 41 years compared with 42 percent and is based on Agricultural Science and Technology Indicators (ASTI) datasets (www.asti. of the total male professional staff. On cgiar.org), Beintema (2006), and Beintema and average, 31 percent of total female staff Di Marcantonio (2009). ASTI is managed by the and 27 percent of total male staff held BSc International Food Policy Research Institute (IFPRI); AWARD is managed by the Consultative Group on degrees. These 15-country averages, again, International Agricultural Research (CGIAR) Gender mask a wide variation across countries (see and Diversity (G&D) Program. Beintema and Di Marcantonio, 2009). 2 Botswana, Burkina Faso, Burundi, Ethiopia, Ghana, Kenya, Malawi, Mozambique, the Niger, The share of women disproportionately Nigeria, Senegal, South Africa, Togo, Uganda and declines on the higher rungs of the career Zambia.
  • 44. 32 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 Mekonnen and Spurling, 1994). Extension Information and extension service agents tend to approach male farmers more often than female farmers because Good and timely information on new of the general misperception that women technologies and techniques is essential do not farm and that extension advice will for farmers when deciding whether or not eventually “trickle down” from the male to adopt an innovation. Although private household head to all other household extension services are playing an increasing members. Extension services are often role in some countries, such as Brazil, China directed towards farmers who are more likely and India, public extension services remain to adopt modern innovations, for example the key source of information on new farmers with sufficient resources in well- technologies for farmers in most developing established areas. As discussed above, women countries. Extension services encompass the are less likely to access resources and may wide range of services provided by experts therefore be bypassed by extension service in the areas of agriculture, agribusiness, providers (Meinzen-Dick et al., 2010). health and others and are designed to Finally, the way in which extension services improve productivity and the overall well- are delivered can constrain women farmers being of rural populations. The provision of in receiving information on innovations. agricultural extension can lead to significant Women tend to have lower levels of yield increases. Yet, extension provision education than men, which may limit their in developing economies remains low for active participation in training that uses a both women and men, and women tend to lot of written material. Time constraints and make less use than men of extension services cultural reservations may hinder women from (Meinzen-Dick et al., 2010). According participating in extension activities, such to a 1988–89 FAO survey of extension as field days, outside their village or within organizations covering 97 countries with sex- mixed groups (Meinzen-Dick et al. 2010). disaggregated data (the most comprehensive Several new and participatory extension study available) only 5 percent of all approaches have been developed and extension resources were directed at women. tested in the past decade in an effort to Moreover, only 15 percent of the extension move away from a top-down model of personnel were female (FAO, 1993). extension service provision to more farmer- In social contexts where meetings between driven services. These approaches can target women and men from outside the family women effectively and increase their uptake nucleus are restricted, a lack of female of innovations (Davis et al., 2009) and will extension agents effectively bars women be discussed in Chapter 5. Participatory from participating. The preference for female approaches that encourage communication extension agents varies by country and marital between farmers and researchers can also status. In Ghana, for example, male and lead to positive feedback loops that allow female farmers in male-headed households researchers to adjust innovations to local have equal contact with extension agents but needs. female farmers in female-headed households Modern information and communication have much less contact, although they are technologies (ICTs) such as radio, mobile willing to speak to agents of either sex (Doss phones, computers and Internet services can and Morris, 2001). In the United Republic of also play an important role in transferring Tanzania, on the other hand, many female information. ICTs offer opportunities for farmers prefer to talk to a female extension accessing and sharing information faster, officer and, by 1997, one-third of extension networking, the mobilization of resources officers were women, up from almost none 15 and educational purposes. Mobile phone years prior (Due, Magayane and Temu, 1997). subscriptions in developing countries have However, even when women have access doubled since 2005. To date, 57 out of 100 to extension services, the benefits may not be inhabitants (up from 23 in 2005) in developing obvious. In Kenya, contact with the extension countries have a mobile phone subscription agent contributed significantly and positively (ITU, 2010). These technologies may be to output on male-managed plots, but not beneficial for rural women whose ability necessarily on female-managed plots (Saito, to travel to distant markets is restricted.
  • 45. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 33 Rural women may face barriers in accessing costs associated with the innovations and ICTs because of their limited education and investment necessary to enhance their financial and time constraints. Locations that productivity, income and well-being. are convenient and appropriate for women Evidence shows that credit markets are not to visit can help improve women’s access (Best gender-neutral. Legal barriers and cultural and Maier, 2007). norms sometimes bar women from holding bank accounts or entering into financial contracts in their own right. Women generally Financial services have less control over the types of fixed assets that are usually necessary as collateral for Financial services such as savings, credit loans. Institutional discrimination by private and insurance provide opportunities for and public lending institutions often either improving agricultural output, food security ration women out of the market or grant and economic vitality at the household, women loans that are smaller than those community and national levels. Many studies granted to men for similar activities (Fletschner, have shown that improving women’s direct 2009; World Bank, FAO and IFAD, 2009). access to financial resources leads to higher In seven out of nine countries in the RIGA investments in human capital in the form of dataset, rural female-headed households children’s health, nutrition and education. are less likely than male-headed households Producers who are unable to cover to use credit (Figure 13). In Madagascar, their short-term expenses or who want for example, the share of female-headed to purchase more productive but more households that use credit is 9 percentage expensive technologies must rely on either points smaller than the share of male-headed credit markets or other credit sources. households who do so. The cases of Ghana Without access to credit, producers may and Panama are noteworthy in that no be unable to bear the risks and up-front gender gap is apparent in the use of credit. FIGURE 13 Credit use by female- and male-headed households in rural areas Ecuador Guatemala Panama Indonesia Nepal Viet Nam Ghana Madagascar Malawi 0 10 20 30 40 50 60 70 80 Percentage of households using credit Female-headed households Male-headed households Note: Calculations made using nationally representative household surveys. The gender gap is calculated as the difference between the percentages of male- and female-headed households that use credit. Sources: FAO, RIGA team, and Anríquez, 2010.
  • 46. 34 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 The gender gap in access to credit is also households typically receive loans only from confirmed by other evidence. In Nigeria, credit cooperatives as opposed to the state for example, 14 percent of males but only banks or wholesalers. Her findings show that 5 percent of females obtain formal credit, women are less likely to use credit than men while in Kenya the percentages are 14 and under equivalent socio-economic conditions 4 for males and females, respectively (Saito, and that they are not always able to rely on Mekonnen and Spurling, 1994). In Uganda, their husbands to help them overcome credit women entrepreneurs receive just 1 percent constraints. These constraints on women’s of available credit in rural areas (Dolan, access to capital have a measurable negative 2004). Also in Uganda, nearly all female- impact on their production capabilities. For headed households reported a desire to example, in addition to the efficiency loss expand agricultural activities but lacked the associated with the husband’s credit constraints, money to purchase land and inputs such as when women are unable to meet their credit seeds, fertilizer and pesticides, and/or to needs their households experience an additional hire-in labour. They cited the lack of access to 11 percent drop in efficiency (Fletschner, 2008). credit as one of the most prominent barriers to livelihood diversification (Ellis, Manuel and Blackden, 2006). Technology In Bangladesh, women received about 5 percent of loans disbursed by financial Access to new technology is crucial in institutions to rural areas in 1980 and only maintaining and improving agricultural slightly more than 5 percent in 1990, despite productivity. Gender gaps exist for a wide the emergence of special credit programmes range of agricultural technologies, including for women in Bangladesh during the machines and tools, improved plant varieties research period (Goetz and Gupta 1996). and animal breeds, fertilizers, pest control Further evidence from Bangladesh suggests measures and management techniques. A that even when programmes succeed in number of constraints, including the gender improving the access of women to credit, gaps described above, lead to gender they may not retain control over the assets: inequalities in access to and adoption of White (1991) found that about 50 percent of new technologies, as well as in the use of loans taken by women were used for men’s purchased inputs and existing technologies. productive activities; Goetz and Gupta (1996) The use of purchased inputs depends on the reported that, on average, women retained availability of complementary assets such as full or significant control over loan use in land, credit, education and labour, all of which only 37 percent of all cases; while Chowdhury tend to be more constrained for female-headed (2009) reported that credit to women from households than for male-headed households. the Grameen Bank was positively and The adoption of improved technologies is significantly correlated with the performance positively correlated with education but is also of male-managed micro-enterprises but not dependent on time constraints (Blackden et al., those managed by females. 2006). In an activity with long turnaround In Eastern Asia, the evidence regarding periods, such as agriculture, working capital bias in credit access is mixed. In China, de is required for purchasing inputs such as Brauw et al. (2008) found that households fertilizers and improved seeds; however, as in which women manage their own farms discussed above, women face more obstacles appear to have almost identical access to relative to men in their access to credit. land and credit relative to male-headed Adoption of improved technologies and inputs households. On the other hand, a joint study may also be constrained by women’s lower by FAO and the United Nations Development ability to absorb risk. Programme (FAO/UNDP, 2002) carried out The evidence points to significant gender in Viet Nam indicates that female-headed differences in the adoption of improved households borrow less, have less access to technologies and the use of purchased inputs formal credit and pay higher interest on across regions (see Peterman, Quisumbing loans than dual-headed households. and Behrman, 2010, for a comprehensive For Latin America, Fletschner (2009) literature review). For example, male- reports that in Paraguay women in farm headed households show much wider use of
  • 47. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 35 fertilizers than their female counterparts in In Burkina Faso, women use less fertilizer per all countries covered (Figure 14). While the hectare than men (Udry et al., 1995). direction of the difference is unambiguous Studies that disaggregate mechanization across technologies and regions, the degree – tools and other farming equipment – by of inequality shows notable variations, gender are rare. This may, in part, be because appearing much more pronounced in modern farming equipment such as tractors Southern Asia (Bangladesh and Pakistan) and and tillers are not commonly available to any in West Africa (Ghana and Nigeria). farmer, especially in sub-Saharan Africa. The Detailed country studies provide deeper share of farmers using mechanical equipment insights. In Ghana, for example, Doss and and tools is quite low in all countries, but it Morris (2001) found that only 39 percent is significantly lower for farmers in female- of female farmers adopted improved crop headed households, sometimes by very wide varieties (compared with 59 percent of male margins (Figure 15). farmers) because they had less access to land, A few studies from the late 1980s and family labour and extension services. Several early 1990s point to gender differences studies from Kenya show that female-headed in ownership of, or access to, tools. In a households have much lower adoption rates Gambian irrigated rice scheme, none of for improved seeds and fertilizers. These the women owned a plough and fewer differences are explained by reduced access than 1 percent owned a weeder, seeder or to land and labour, lower education levels multipurpose cultivation implement; the and limited access to credit markets (Kumar, proportions of men owning these tools 1994; Saito, Mekonnen and Spurling, 1994; were 8, 12, 27 and 18 percent, respectively Ouma, De Groote and Owur, 2006). Credit (von Braun, Hotchkiss and Immink, 1989). constraints also limit the access of female- According to data from a household survey headed households to fertilizers in Benin and across three Kenyan districts, the value of Malawi (Minot, Kherallah and Berry, 2000). farm tools owned by women amounted to FIGURE 14 Fertilizer use by female- and male-headed households Bolivia Ecuador Guatemala Nicaragua Panama Bangladesh Nepal Pakistan Tajikistan Viet Nam Ghana Madagascar Malawi Nigeria 0 10 20 30 40 50 60 70 80 90 Percentage of households using fertilizers Female-headed households Male-headed households Note: Calculations made using nationally representative household surveys. Differences between female- and male-headed households are significant at the 95 percent confidence level for all countries. Sources: FAO, RIGA team, and Anríquez, 2010.
  • 48. 36 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 15 Mechanical equipment use by female- and male-headed households Ecuador Guatemala Nicaragua Panama Bangladesh Indonesia Nepal Tajikistan Viet Nam Ghana Madagascar Malawi Nigeria 0 5 10 15 20 25 30 35 40 45 50 Percentage of households using mechanization Female-headed households Male-headed households Note: Calculations made using nationally representative household surveys. Differences between female- and male-headed households are significant at the 95 percent confidence level for all countries. Sources: FAO, RIGA team, and Anríquez, 2010. only 18 percent of the tools and equipment It is important to note that not all types owned by male farmers (Saito, Mekonnen of female-headed households are equally and Spurling, 1994). constrained in their access to technology. On In a more recent study of productivity small farms in Kenya, households headed by differences by gender in a rice irrigation single, divorced or widowed women are the scheme in Central Benin, researchers noted least likely to use animal traction. In contrast, that equipment such as motor cultivators female-headed households in which the used for ploughing and transport were husband lives elsewhere are more likely to managed by groups, but women’s groups use animal traction and hired labour, because were unable to start ploughing until the they still benefit from their husband’s drivers had completed work on men’s fields. name and social network and often receive As a consequence of the delays in ploughing remittances from him (Wanjiku et al., 2007). and planting, women faced yield losses and could not participate in a second cropping season (Kinkingninhoun-Mêdagbé et al. Key messages 2010). Gender differences in the use of farm equipment may have further implications. • Across diverse regions and contexts, Quisumbing (1995), for example, concludes women engaged in agriculture face that farmers with more land and tools are gender-specific constraints that limit more likely to adopt other technologies, thus their access to productive inputs, highlighting the complementarities among assets and services. Gender gaps are agricultural inputs. observed for land, livestock, farm labour, Furthermore, lack of access to education, extension services, financial transportation technology often limits the services and technology. mobility of women and their capacity to • For those developing countries for which transport crops to market centres (Box 7). data are available, between 10 percent
  • 49. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 37 BOX 7 Smallholder coffee production and marketing in Uganda Coffee is Uganda’s largest export, much smaller scale, women sold smaller providing employment (directly and amounts than men (only 47 kg, on average, indirectly) to an estimated 5 million people compared with 151 kg for men). (Bank of Uganda, 2001; Kempaka, 2001). Most smallholders sold their coffee in Smallholders’ coffee is usually intercropped the form of dry cherries locally known with staples such as banana, plantain, as kiboko, which would then be milled beans, sweet potatoes and maize. Simple by the traders who bought the coffee. farming methods are normally used to Some farmers transported their coffee to produce coffee; purchased inputs such as market, which allowed them to sell it at fertilizer or pesticides are used minimally a higher price. Members of male-headed and irrigation is rare. households were more likely than those A study by Hill and Vigneri (2009) of female-headed households to travel to draws on a sample of 300 coffee-farming market to sell their coffee. Fifteen percent households that were surveyed in 1999 of the transactions made by male-headed and 2003. Twenty-three percent of the households took place in the nearby coffee households were headed by females market, compared with only 7 percent (mainly widows, but also unmarried, of transactions by women. This may be separated and divorced women). Female- because men were more likely to own a headed households had less labour, bicycle and could therefore travel to the land and coffee trees than male-headed market more easily than women. Farmers households; they also had lower levels of received a higher price for their coffee if wealth and education. Women household they chose to mill it at the market before heads tended to be older; many were selling it. Only 3 percent of transactions wives who had taken over when their were for milled coffee, all of which were husband had died. As a result of these made by male-headed households. basic differences in scale, liquidity and The study concludes that gender human capital, we may expect crop choice, differences in marketing are largely production methods and access to markets explained by the fact that women market to be quite different for male- and smaller quantities of coffee and do not female-headed households. own bicycles. It also finds that a major The share of labour allocated to coffee constraint facing women is their relative production and the proportion of trees difficulty in accessing marketing channels harvested were comparable between male- that allow added value. By engaging in and female-headed households, as was the marketing channels in which they add yield per producing tree. However, because value, male-headed households received female-headed households farmed on a 7 percent more per kilogram of coffee. and 20 percent of all land holders are half to two-thirds the size of farms women, although this masks significant operated by male-headed households. differences among countries even • The livestock holdings of female farmers within the same region. The developing are much smaller than those of men in countries having both the lowest and all countries for which data are available, highest shares of female land holders are and women earn less than men from in Africa. their livestock holdings. Women are • Among smallholders, farms operated by much less likely to own large animals, female-headed households are smaller such as cattle and oxen, that are useful as in almost all countries for which data are draught animals. available. The gap is negligible in some • Farms run by female-headed households countries, but in others farms operated have less labour available for farm work by female-headed households are only because these households are typically
  • 50. 38 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 smaller and have fewer working-age adult • Smallholders everywhere face constraints members and because women have heavy in accessing credit and other financial and unpaid household duties that take services, but in most countries the share them away from more productive activities. of female smallholders who can access • Education has seen improvements in credit is 5–10 percentage points lower gender parity at the national level, than for male smallholders. Access to with females even exceeding male credit and insurance are important for attainment levels in some countries, but accumulating and retaining other assets. in most regions women and girls still lag • Women are much less likely to use behind. The gender gap in education is purchased inputs such as fertilizers particularly acute in rural areas, where and improved seeds or to make use of female household heads sometimes have mechanical tools and equipment. In less than half the years of education of many countries women are only half as their male counterparts. likely as men to use fertilizers.
  • 51. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 39 4. Gains from closing the gender gap Many studies show that yields on plots based discrimination. Countries with lower managed by women are lower than those levels of gender inequality tend to achieve managed by men. This is not because higher average cereal yields than countries women are worse farmers than men. Indeed, with higher levels of inequality (Figure extensive evidence shows that women are 16). Of course, the relationship shows only just as efficient as men. They simply do not correlation, not causation, and the direction have access to the same inputs. If they did, of causality could run in either direction (or their yields would be the same as men’s, they in both directions). In other words, more would produce more and overall agricultural equal societies tend to have more productive production would increase. agriculture, but more productive agriculture The relationship between gender can help reduce gender inequality. equality and agricultural productivity can Research surveyed below confirms that be explored using OECD’s index of Social closing the gender gap in agriculture can Institutions and Gender Inequality (SIGI) improve agricultural productivity, with (OECD, 2010). The SIGI index reflects social important additional benefits through and legal norms such as property rights, raising the incomes of female farmers, marital practices and civil liberties that increasing the availability of food and affect women’s economic development. A reducing food prices, and raising women’s lower SIGI indicates lower levels of gender- employment and real wages. FIGURE 16 Cereal yield and gender inequality Cereal yield (tonnes/ha) 4 3.5 3 2.5 2 1.5 1 0.5 0 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th SIGI group: 1st = least gender inequality to 10th = greatest gender inequality Notes: Gender inequality is a measure used by the Social Institutions and Gender Index (SIGI), a composite measure of gender discrimination based on social institutions, constructed by the OECD Development Centre. Sources: Cereal yield: FAO, 2010b; SIGI group: OECD, 2010.
  • 52. 40 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 labour, the plots controlled by women used Productivity of male and female less of all other inputs: men’s and children’s farmers labour, draught animal labour and organic and chemical fertilizers. Women’s yields Many studies have attempted to assess were lower than men’s for a variety of whether female farmers are as productive crops – 20 percent lower for vegetables and as male farmers. These studies measure 40 percent lower for sorghum – but the productivity in a variety of ways, but the difference was explained entirely by their most common method is based on output lower use of productive inputs, which in turn per hectare of land, or yield. Simply was a result of gender-specific social norms. comparing yields on men’s and women’s The authors estimated that increasing input farms can reveal differences between the use on women’s plots could increase overall two groups – women typically achieve output by 10–20 percent (Udry et al., 1995). lower yields than men do – but it does not Further analysis of the same data found that explain why. The most thorough studies also overall household production could have attempt to assess whether these differences been almost 6 percent higher if resources are caused by difference in input use, such were reallocated towards women’s plots as improved seeds, fertilizers and tools, or (Udry, 1996). other factors such as access to extension Two additional studies from Burkina services and education. The vast majority Faso provide a deeper understanding of of this literature confirms that women are these issues. The first found that female just as efficient as men and would achieve farmers produced 15 percent lower value the same yields if they had equal access to per hectare than male farmers. It also found productive resources and services. that female farmers needed advice from A thorough literature search identified female agricultural extension workers – not 27 studies that compare the productivity just more inputs – in order to achieve higher of male and female farmers.10 These yields, confirming the complementarities studies covered a wide range of countries among the broad range of assets and services (primarily, but not only, in Africa), crops, required for agricultural production (Bindlish, time periods and farming systems, and Evenson and Gbetibouo, 1993). The second used various measures of productivity and reconsidered the data from Udry (1996) efficiency. Despite this variety, most found and supplemented them with more recent that male farmers achieved higher yields nationally representative data. It found than female farmers. The estimated yield that households located in less favourable gaps ranged widely but many clustered production zones or in areas suffering around 20–30 percent, with an average of from drought tended to allocate resources 25 percent.11 between male- and female-managed plots Most of the studies found that differences more efficiently than households in more in yields were attributable to differences in favourable areas, perhaps because the risk input levels, suggesting that reallocating associated with being inefficient was higher inputs from male to female plots can for them (Akresh, 2008). increase overall household output. Several Research in the Ethiopian highlands found studies showed this explicitly. Because that female-headed households produced this literature is complex and somewhat 35 percent less per hectare, in value terms, contentious, it is summarized below. than male-headed households but the One of the most influential studies in differences were due to lower levels of input this field comes from Burkina Faso. The use and less access to extension services by authors compared 4 700 agricultural plots the female farmers (Tiruneh et al., 2001). In in six villages. With the exception of own- the same region, yields for barley and other cereals were found to be 50 percent higher 10 For more detailed surveys of this literature, see for farms operated by men because farms Quisumbing (1996) and Peterman, Quisumbing and run by female-headed households had only Behrman (2010). half the male labour and less than one-third 11 Not all of the 27 studies quantified the yield gap. Some provided estimates for a single crop while others reported of the amount of draught animal power on multiple crops. (Holden, Shiferaw and Pender, 2001).
  • 53. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 41 Women in Ghana were found to be of lower quality or higher price (Timothy and as efficient as men in maize and cassava Adeoti, 2006). production, but they achieved lower yields Additional studies in sub-Saharan Africa and earned lower profits because they from Cameroon (Kumase, Bisseleua and could not maintain the fertility of their land Klasen, 2008), Benin (Kinkingninhoun- (Goldstein and Udry, 2008). People who are Mêdagbé et al., 2010), Côte d’Ivoire (Adesina disadvantaged in the social and political and Djato, 1997) and Zimbabwe (Horrell and networks of their villages – like many female Krishnan, 2009) also overwhelmingly support household heads – are more likely to have the conclusion that differences in farm their land expropriated if they allow it to yields between men and women are caused remain fallow, so they tend to keep their primarily by differences in access to resources land under cultivation continuously, eroding and extension services.12 soil fertility (Goldstein and Udry, 2008). Evidence from other regions is relatively Several studies from Ghana also confirm rare because farming operations are less that male and female cocoa producers have likely to be segregated by gender than is the same yields when input use is the same the case in Africa, but the available studies (Quisumbing and Otsuka, 2001b; Hill and generally support the finding that female Vigneri, 2009). farmers are at least as efficient as their Men producing maize, beans and cowpeas male counterparts. For example, female- in Kenya achieve higher gross value of managed farms in Nepal produce less value output per hectare than women, but the per hectare than male-managed farms, but difference is accounted for by differences in the differences are nearly all accounted for input use (Saito, Mekonnen and Spurling, by lower input use (Thapa, 2008). Female- 1994). In western Kenya, female-headed managed farms in China are at least as households were found to have 23 percent profitable as those run by men, according to lower yields than male-headed households, data from the China National Rural Survey but the difference was caused by less-secure (Zhang, De Brauw and Rozelle, 2004). access to land and lower education levels Some studies compare labour productivity (Alene et al., 2008). An earlier study of rather than yields, but the results are smallholder farmers in western Kenya found consistent with the finding that yield that women’s maize yields were 16 percent differences are caused by differences in input lower than men’s, largely because they used use. The labour productivity of female farm substantially less fertilizer (Ongaro, 1990). workers in Bangladesh is at least as high as A nationally representative study in that of male workers when input use is the Malawi found that maize yields were same (Rahman, 2010). Labour productivity 12–19 percent higher on men’s plots, but studies for oil palm in Indonesia (Hasnah, when women were given the same level of Fleming and Coelli, 2004), for rice in Nepal fertilizer for use on experimental plots, they (Aly and Shields, 2010) and for vegetables in achieved the same yields (Gilbert, Sakala and Turkey (Bozoglu and Ceyhan, 2007) all show Benson, 2002). that female labour is at least as productive Considerable evidence is available from as male labour when differences in irrigation Nigeria from several states and for a wide and seed type are considered. variety of crops. In Oyo State, male and female farmers growing maize, yam, cassava, vegetables and legumes were found to be Production gains from closing the equally productive (Adeleke et al., 2008). In gender gap Osun State, female rice producers achieved 66 percent lower yields than male farmers If gender-specific differences in input use but the difference was attributable to could be overcome and female farmers could differences in input use (Oladeebo and achieve the same yields as male farmers, the Fajuyigbe, 2007). Similarly, in Ondo and Ogun States, female small-scale cassava 12 Some studies could not fully account for yield differences between male and female farmers because they did not farmers achieved lower yields and lower consider all the resource gaps women face (Zavale, Mabaye returns than their male counterparts because and Christy [2006], Uaiene and Channing [2009], and Lilja, they used fewer inputs and purchased inputs Randolph and Diallo [1998]).
  • 54. 42 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 evidence suggests that the production gains countries where the gender gap is wider. could be substantial. The potential gains Increasing women’s access to land as well as cannot be calculated precisely because the complementary inputs in that case would necessary data are not available; however, generate broader socio-economic benefits a reasonable range can be estimated based than those captured by this analysis. on the yield gaps identified in the studies This approach provides admittedly discussed above and the amount of farm very rough estimates, but they suggest land that women manage. that closing the gender productivity gap As noted above, studies of the yield gap could increase agricultural output in the between male and female farmers provide developing world by a significant amount. estimates averaging 20–30 percent, and most Increased production would also imply attribute the difference to lower levels of increased food availability and reductions input use. Although most of these studies in undernourishment. The standard pertain to sub-Saharan Africa, similar input methodology used by FAO to estimate the gaps have been documented for all regions number of people who are undernourished in Chapter 3. Therefore, it is reasonable to calculates the average daily dietary energy assume that a similar range of yield gaps supply available for consumption in each exists in other regions. Closing the input country and applies country-specific criteria gap on the agricultural land held by women for its distribution and thresholds for could increase yields on their land to the minimum per capita energy requirements levels achieved by men. This would imply (see FAO, 2002 for details). People who an increase in production of 20–30 percent fall below this minimum threshold are on their land, and increases at the national considered chronically undernourished. level proportionate to the amount of land Domestic food production is a key controlled by women. This would increase component of the dietary energy supply, agricultural output in the developing so – assuming that the additional output countries for which data are available by an from closing the gender gap is consumed average of 2.5–4 percent.13 Assuming that domestically – closing the gender yield gap the input and yield gaps are representative could have a direct impact on reducing the of other developing countries, this would number of people who are undernourished. imply global gains of a similar magnitude. Inserting the potential output gains Of course, the potential production calculated above into the formula for gains calculated by this method are based estimating the number of undernourished on the existing distribution of land and a provides a rough quantitative estimate of stylized yield gap of 20–30 percent. This how closing the gender gap in agriculture implies that countries where women control could contribute to reducing hunger. If proportionately more land could achieve yield gaps of 20–30 percent were closed the greatest potential gains. It may be the and domestic production increased by 2.5– case, however, that the overall gender gap 4 percent, the number of undernourished in access to agricultural resources is, in fact, people in the countries for which data are wider where women control less land. The available could decline by 12–17 percent.14 actual gains from closing the gender gap An estimated 925 million people in the world in access to resources would be greater in were undernourished in 2010, of which 906 million were in developing countries (FAO, 2010g), Gains of this magnitude could 13 Data on the share of women agricultural holders are available for 52 countries. The methodology for therefore equate to 100–150 million fewer calculating potential gains starts with the definition of people living in hunger. For countries where output (Q) as yield (Y) times area (A), Q = Y*A. Next, for hunger is more widespread and women play the 20 percent productivity gap scenario, assume that a major role in the agriculture sector, the women farmer’s yields are only 80 percent those of men, i.e. Yf = 0.8*Ym. (The subscripts f and m denote female proportional declines could be even greater. and male, respectively.) Now write Q=Y*A as Q = Yf *P*A + Ym*(1-P)*A, where P is the share of land cultivated by women farmers. Solve this problem for Ym and then use Yf = 0.8*Ym to obtain Yf. Assuming the gender gap in 14 Data for both the share of women agricultural holders productive assets is closed, set Yf equal to Ym and find the and the number of people undernourished are available for new output level, Q*. 34 countries.
  • 55. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 43 These potential output gains would contributes positively and significantly only be the first, direct, effect. Over time, to household food consumption (Garcia, higher productivity would have additional 1991). This was reinforced by evidence impacts such as increased demand by from Brazil, which showed that maternal farmers for labour and locally produced income exerts a larger effect on children’s goods and services (Hayami et al., 1978; nutritional outcome indicators than paternal FAO, 2004). Additional output could result income and that women spend considerably in lower commodity prices, depending on more than men on education, health, the responsiveness of demand and the and household services (Thomas, 1997). In degree of trade openness. Most households extended family households in Mexico, the in developing countries, including in rural impact of increasing family income on the areas, are net food buyers and would gain nutritional status of children depends on from a fall in staple food prices. Farm who earns the income; higher earnings by incomes could suffer, on the other hand, any female household member – not only unless markets are sufficiently developed so mothers – has substantial positive impacts as to handle the additional supply. on child nutrition, while this is not the case for male income earners (Djebbari, 2005). More recent evidence from Malawi confirms Other social and economic benefits that increasing women’s – but not men’s – of closing the gender gap access to credit increases total household expenditures on food and improves the long- In addition to increases in production and term food security of young female children income, closing the gender gap in agriculture (Hazarika and Guha-Khasnobis, 2008). would generate broader social and economic The fact that gender inequality is benefits by strengthening women’s direct particularly severe in Southern Asia helps access to, and control over, resources and explain, at least partly, why rates of child incomes. Evidence from Africa, Asia and Latin malnutrition there are twice those found America consistently shows that families in sub-Saharan Africa (Smith et al., 2003). benefit when women have greater status Indeed, despite surpassing sub-Saharan and power within the household. Increased Africa in terms of national income, control over income gives women a stronger democracy, food supplies, health services bargaining position over economic decisions and education, Southern Asia still trails in regarding consumption, investment and child malnutrition. This has been labelled production. When women have more the “Asian enigma”, which finds women’s influence over economic decisions, their status, sanitation and urbanization to be families allocate more income to food, the key factors in narrowing the gap in health, education, children’s clothing and children’s nutritional status. Recent evidence children’s nutrition.15 Social safety-net from Bangladesh confirms that children’s programmes in many countries now target long-term nutritional status is higher women specifically for these reasons (Box 8). in households where women are more A large number of studies have linked empowered (Bhagowalia et al., 2010). women’s income and greater bargaining Improved gender equality in access to power within the family to improved child opportunities and returns to assets not only nutritional status, which in turn influences improve nutrition, health and education health outcomes and educational attainment outcomes, but can also have a long-lasting (Smith et al., 2003). Evidence from the impact on economic growth by raising Philippines provided some of the earliest the level of human capital in society.16 data showing that increasing the share Closing the gender gap spurs economic of household income earned by mothers development, largely through the impact of female education on fertility, child 15 Important studies in this field include Behrman and Deolalikar (1988), Behrman and Wolfe (1989), Kennedy and Peters (1992), Kennedy and Haddad (1994), Hoddinott 16 Important studies in this field include Dollar and Gatti and Haddad (1995), Thomas (1997), Haddad (1999), Katz (1999), Klasen (2002), Knowles, Lorgelly and Owen (2002), (2000), Quisumbing and Maluccio (2000), Smith et al. Kalaitzidakis et al. (2002), Lagerlöf (2003) and Klasen and (2003) and Doss (2005). Lamanna (2009).
  • 56. 44 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 BOX 8 Targeting transfer payments to women for social benefits Conditional transfer programmes are a the education, nutrition, and /or well-being type of safety net programme in which of their children. Post-factum evaluations cash or benefits in kind are transferred to of conditional transfer programmes have generally poor households on condition confirmed this to be the case: the impact that the household undertake certain on spending patterns goes beyond the types of human capital investment for simple income effect of the transfer, with the benefit of their children. Women are recipient households spending a larger often targeted as the recipients of such proportion of their incomes on food payments because evidence shows they (Schady and Rosero, 2008) and a relatively are more likely than men to prioritize larger proportion on more nutritious food child nutrition. The types of investments (Macours, Schady and Vakis, 2008). generally considered are in health – i.e. An implicit, yet important, idea pre- and post-natal health care, health underlying these programmes is that by check-ups or attendance at health directing the transfers to mothers, they clinics – and in education – generally strengthen the bargaining position of measured by enrolment and attendance women in the intra-household decision- rates. Conditional transfer programmes making process. Some conditional have rapidly gained popularity in the transfer programmes successfully also developing world. Starting from the target gender inequality directly. In Oportunidades (formerly known as Bangladesh and Pakistan, programmes PROGRESA – Education, Health and exist to promote girls’ enrolment in public Nutrition Programme) programme in education. In Bangladesh, the Female Mexico in 1997, they have expanded Secondary School Assistance Project worldwide, with all developing regions (FSSAP) provides a stipend to girls aged having some active conditional transfer 11–18 years for attending secondary programme, although with the largest school, while in Pakistan, the Punjab prevalence in Latin America. Education Sector Reform Programme Conditional transfer programmes can (PESRP) provides “scholarships” for be used directly and indirectly to address girls aged 10–14 to attend school. Both gender inequities. With the exception of a programmes have been very successful few secondary school programmes, in the in increasing enrolment: Khandker, great majority of them the beneficiaries are Pitt and Fuwa (2003) estimate that the the mothers. This choice is founded on the FSSAP increased the enrolment of girls overwhelming evidence that, when women by 12 percentage points, while the PESRP and mothers control a higher proportion increased it by 11 percentage points, of household income, families tend to according to an evaluation by Chaudhury spend a higher share of their budgets on and Parajuli (2010). mortality and the creation of human capital men and women, will again work to raise in the next generation. Falling fertility the level of human capital available in rates will, after some years, lead to what the working population. These growth Bloom and Williamson (1998) have termed studies suffer from the usual limitations: the “demographic gift”. The working-age it is impossible to assign the direction of population will grow faster than the rest of causality, and it could also be the case the population, reducing dependency rates that higher growth causes countries to and thus benefiting per capita growth. reduce gender inequality by economically It is also true that removing the gender empowering women. Nonetheless, the point gap in access to opportunities widens the remains that closing the gender gap in pool of talent available, which, assuming educational and employment opportunities that the talent is distributed equally among would boost long-term growth.
  • 57. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 45 • Increasing agricultural production Key messages by this magnitude could reduce the number of undernourished people • Female farmers are just as efficient as by 12–17 percent, and would imply male farmers but they produce less significant progress towards achieving because they control less land, use fewer MDG 1C. This highlights the synergies inputs and have less access to important that exist between promoting gender services such as extension advice. equality and reducing extreme poverty • Closing the gender gap in access and and hunger. use of productive resources and services • When women control additional would unlock the productivity potential income, they spend more of it than of women and could increase output men do on food, health, clothing and substantially. Closing the gap could education for their children. This has increase agricultural output in the positive implications for immediate developing world by 2.5–4 percent, on well-being as well as long-run human average, with higher gains in countries capital formation and economic growth where women are more involved in through improved health, nutrition and agriculture and the gender gap is wider. education outcomes.
  • 58. 46 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 5. Closing the gender gap in agriculture and rural employment Closing the gender gap in agriculture is them. In the parts of sub-Saharan Africa not an easy task, but progress can be made where customary property regimes prevail, and simple interventions can sometimes community leaders tend to favour males over be very powerful. Carefully designed females in the allocation of land, both in policies, strategies and projects can work terms of quantity and quality. Where private within existing cultural norms, through property prevails, cultural norms generally the public and private sectors, in ways that dictate that men own and inherit land while benefit both women and men (Box 9). women gain access to land through their Specific recommendations for closing the relationship with a male relative. gender gap in access to land, rural labour markets, financial services, social capital and Eliminate discrimination under the law technology include the steps outlined below. Where statutory legal rights to land remain gender-biased, a key strategy is to review and reform all national legislation that Closing the gap in access to land17 relates to land and natural resources. Although land laws are the starting point, Governments have long recognized the related legislation should also be considered. importance of secure land tenure in Family and marriage laws, inheritance promoting equitable, sustainable agricultural provisions and housing law are all important development. Women have not always legal areas that play a supporting role in benefited from general land distribution and ensuring equitable treatment of men and titling efforts, however, and in some cases women in control over land.18 have seen their customary rights eroded as formal rights have been extended to male Recognize the importance and power of heads of household. Many governments have customary land rights attempted to strengthen women’s tenure Many countries have extended formal legal rights within marriage and as individuals, rights to women over land inheritance and but these efforts are often frustrated by a ownership, but customary practices – and combination of legal and cultural practices the inability of many women to assert that still favour men. their legal rights – mean that formal legal In Latin America, for example, inheritance provisions are often not followed. In many is the most frequent source of transfer of countries, tradition is stronger than law ownership of land, but daughters are much when it comes to land issues. Opposition less likely than sons to inherit land. Many from land reform authorities, peasant unions, countries in the region have instituted legal village authorities and male household reforms that have strengthened married heads can frustrate land reform efforts to women’s land rights, but land-titling efforts extend legal land rights to both single and have not always facilitated the practice of married women. Legal rights are difficult to including both husbands’ and wives’ names. enforce if they are not seen as legitimate; In Asia, women typically have legal rights to thus recognizing customary land rights and land ownership, but often struggle to assert working with community leaders is essential to ensure that women’s rights are protected. 17 This section is based on FAO (2010h), which provides an extensive review of the relevant literature. Important studies in this field include Agarwal (1994), Agarwal (2003), 18 Additional information on women and their status under Lastarria-Cornhiel (1997), Deere (2003), Deere and León the law is available at the World Bank website “Women, (2003), and Deere and Doss (2006). business and the law” (http://wbl.worldbank.org/).
  • 59. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 47 BOX 9 Mama Lus Frut: working together for change Palm oil production in Papua New Guinea collection to take into account women’s is dominated by smallholder farmers, time constraints. Then they distributed and harvesting oil palm trees is highly special nets that made it easier to carry differentiated by gender: men cut fresh the loose fruits to the roadside. Neither fruit bunches from the trees, while women initiative was successful, because they did collect loose fruits from the ground and not correctly assess why women were not carry them to the roadside where they collecting the fruit. are picked up by operators from the mill. Finally, the Mama Lus Frut scheme These gender roles are firmly engrained in was introduced in 1997 to ensure that the local culture and institutions. women received payment for their work. Family labour is mobilized for the Women received individual harvest nets harvest. While it was implicitly assumed and harvest payment cards, and they in the past that the household head received their own monthly income would compensate family members for based on the weight of the fruit they their labour with the income gained from collected, deposited directly into their oil palm production, in reality, female personal bank accounts. As a result, the household members were often not being number of women participating in the compensated for their work. In many cases, scheme more than doubled and the this led to intra-household struggles and amount of loose fruits delivered to the to women withdrawing their labour from mills increased significantly. By 2001, loose fruit collection and focusing instead 26 percent of smallholder income from on vegetable production, which allowed oil palm was directly paid to women. Men them to earn, and keep, an income. reacted positively because the gender The local oil palm industry realized that division of labour remained unchanged between 60 and 70 percent of loose fruit and intra-household conflicts over palm oil were not being collected. The industry harvesting decreased. tried to raise the share of loose fruits in total harvest through several initiatives. Sources: Kosczberski, 2001, and Warner and First, they delayed the timing of loose fruit Bauer, 2002. Indeed, strengthening traditional use-rights and courts. Gender-balanced employment for widows and divorced women may provide in these institutions can also help. Where more secure tenure for them even in cases appropriate, officials’ performance should where there is resistance to full ownership. be evaluated against gender-related targets. The involvement of women’s organizations in Educate officials and evaluate them on the process can facilitate the achievement of gender targets gender equity targets. Furthermore, gender Local land officials may be unaware of targets for access and tenure security should gender equity laws and objectives or lack be monitored and officials held accountable the mechanisms, tools and will to implement for meeting them. them. Legislation needs to be supported In Nicaragua the property legalization by regulations and gender-specific rules process, which the women’s affairs office and guidelines that educate officials in helped coordinate, included gender agriculture ministries, land institutions and sensitization training for officials and other agencies regarding the implementation information campaigns on the inclusion of of the gender position of the law. Relevant women in the process (FAO, 2010h). This training is also required for staff in the has helped raise awareness and acceptance various institutions that carry out and enforce among men and women of women’s land land rights, including land registries, cadastral rights, although several rounds of training offices, titling agencies, land magistrates were necessary.
  • 60. 48 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 Educate women regarding land rights of women in local government. The 2003 Raising women’s legal literacy, increasing constitution mandates that 30 percent of all the dissemination and accessibility of decision-making representatives be women. information and establishing supporting Similarly, in the United Republic of legal services are essential in promoting Tanzania, village land councils, which settle gender equity in land programmes. Legal land disputes, comprise seven members, of literacy means that women are aware of whom three must be female (Ikdahl, 2008). their legal rights and know how they can be Ethiopia’s land certification process has enforced and protected. Officials responsible been hailed as effective, low-cost, rapid and for implementing land programmes must transparent, and gender equity goals have actively educate both men and women been advanced because land administration regarding gender equity provisions and committees at the local level are required to the possibility of joint titling, rather than have a least one female member. treating the decision as a private matter In the Lao People’s Democratic Republic, between spouses (Ikdahl, 2008; Brown, 2003). women were not receiving titles until the Civil society organizations can be Lao Women’s Union started to participate instrumental in promoting legal literacy. In in the land-titling programme. The Union Mozambique, when land legislation was works at the national and local levels and integrated into literacy programmes or when has been active in informing both men and non-governmental organizations (NGOs) women about the titling process and their distributed land law information repeatedly legal rights, as well as helping to formulate over a long time, women were more likely to gender-sensitive procedures and train local know their rights to land (FAO, 2010h). field staff in their application. Precisely because they are so important, Women must be an integral part of the land tenure issues are often contentious, and implementation of land programmes. women seeking to assert their rights may Training community members as paralegals, be subject to pressure from their families topographers and conflict mediators can and communities. The provision of legal help build community skills and increase the protections and affordable legal services probability that women’s concerns will be are vital in this respect. Mobile legal clinics addressed. with staff trained in land issues may be a useful solution during land formalization Adjust bureaucratic procedures programmes. Simple steps such as making space for two names on land registration forms can Ensure that women’s voices are heard be a powerful tool for encouraging joint Meaningful representation constitutes an titling and protecting the rights of women important step towards helping women within marriage. In Brazil, for example, gain access to established rights. Women’s women were guaranteed equal rights to organizations can be effective in promoting land distributed through agrarian reform local participation, building a consensus and in 1988, but few women were registered as raising consciousness at all levels. The role beneficiaries because the registration forms played by women’s organizations is especially mentioned them only as dependants. The valuable as women are generally not well forms were changed in 2001 to include the represented in decision-making bodies, and names of both spouses as co-applicants or they are often instrumental in pressuring for beneficiaries (Deere, 2003). government programmes to include women Rural women often lack the documents as equal participants. (such as birth records) required to obtain Rwanda provides an example of how state land titles, so facilitating access to such institutions and civil society organizations can documents may be necessary. Placing work together to secure women’s land rights. photographs of owners on land certificates Rwanda successfully reformed its inheritance can reduce the likelihood of cheating and and land tenure legislation and now has manipulation. Ethiopia’s land programme, among the best legal conditions for gender for example, requires that certificates for equity in these areas. Enactment of the new women bear their photographs to help laws was made possible by the participation ensure that they retain control over their
  • 61. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 49 land. This measure has been credited with reproductive roles, which reflects social improving their security of tenure and has norms and child-rearing responsibilities. As facilitated the renting-out of land by women noted in Box 3 (see page 14), in most rural (Deininger et al., 2007). areas women undertake most of the work related to child care, food preparation Gather sex-disaggregated data for and other household responsibilities such policy design and monitoring as collecting fuel and water. Women are Gathering sex-disaggregated data can help also heavily involved in unpaid agricultural improve the design and effectiveness of production. When all household activities land-titling programmes. In Cambodia, for are taken into account, women generally example, a land-titling project conducted a work longer hours than men. Women face social assessment before implementation, multiple trade-offs in the allocation of their revealing useful insights into gender time and, without policies and investment in inequality and land ownership that were labour-saving technologies, labour market subsequently used to inform the programme participation is often not an option – even implementation. The fact that 78 percent when the opportunities are available. of new titles were issued in the joint names Labour-saving technologies are discussed of husbands and wives testifies to project’s separately in the section on “Closing the success in ensuring the inclusion of women. technology gap” (see page 56). Improving women’s labour market participation also requires that governments Closing the gap in rural labour create a good investment climate through markets19 strengthening property rights and providing public goods such as roads, electricity and For most women in developing countries water. Women’s unequal access to assets and labour is their key asset. Agriculture is of resources such as land limits their options for particular importance as a source of self- and self-employment. Easier access to firewood, wage-employment, especially for women water and markets relaxes women’s time (and men) who lack training or resources constraints and can make an appreciable for employment in other sectors. Viewed difference in their ability to participate in in this context, agriculture also contributes employment and self-employment. Women to poverty alleviation. Agricultural need to be involved in investment planning growth generates demand for labour and right from the beginning. In Peru, for adds upward pressure on real wages for example, women’s direct participation in unskilled labour. Both of these have positive the design of a rural roads project ensured implications for poor men and women, but that greater priority was given to their especially so for the latter (see Chapter 3). needs. Upgrading was not restricted to roads The principle that both employment and connecting communities, but was extended job quality matter is reflected in target 1B to many non-motorized transport tracks of MDG 1: “Achieve full and productive used mostly by women and ignored by other employment and decent work for all, road programmes. The resultant reduction in including women and young people”. The time spent obtaining food and fuel supplies United Nations’ “Decent Work” agenda for enabled women to participate more in achieving MDG 1B promotes four objectives markets and fairs, and 43 percent of them that include employment generation as reported earning higher incomes (World well as social protection, enforcement of Bank, 2008). labour standards and regulations, and social dialogue. Reduce gender inequalities in human capital Target women’s multiple trade-offs Women remain significantly overrepresented Perhaps the gender issue that has most among the illiterate (UN, 2009). Improved relevance for labour market participation access to education and better-quality is that of time allocated to productive and education will help reduce some of the wage gap and, more importantly, allow women 19 The analysis in this section draws on Termine (2010). to diversify by widening the opportunities
  • 62. 50 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 available to them. In countries where part of the Ethiopian Government’s food agriculture is a major source of employment security strategy and reaches over 7 million for women, skill building should address chronically food-insecure individuals. Support relevant skills and knowledge gaps and focus for pregnant and lactating women is one on extension services and vocational training. important benefit for many women. At the A higher probability of obtaining a job in a community level, the creation of water- particular sector will also influence parents’ harvesting facilities and land rehabilitation educational choices for their children. In initiatives is a positive development for the Philippines, women are more likely to both women and men. Women also gain obtain non-farm employment than men and from the programme through the change this partly explains the higher educational in men’s attitudes towards women’s work attainment of girls (Quisumbing, Estudillo capabilities as a result of regular joint work and Otsuka, 2003). on public works. The programme has helped Policy interventions need to focus increase household food consumption and on school enrolment for girls, health contributes to the costs of providing for interventions such as immunization and children’s needs, including clothing and nutritional interventions that target women’s education and health-care costs (Holmes specific needs throughout their life cycle. and Jones, 2010). These benefits have been Conditional transfer programmes (see particularly valuable in the case of female- Box 8, page 44), which are often targeted headed households who, prior to the at the women in the household, have been programme, had fewer alternative avenues used successfully to improve the education, for support. health and nutrition of children and women In India, the National Rural Employment (Quisumbing and Pandolfelli, 2010). Guarantee Act (NREGA) was implemented in 2005 with the goal of improving the Capitalize on public works programmes purchasing power of rural people. It Informal labour is a major source of income provides a legal guarantee for 100 days of for unskilled women in general, but employment per year for adult members of especially so in times of crisis. Public works any rural household who are willing to do schemes can provide support to unskilled unskilled manual work on public projects workers, including women. These are public in return for the statutory minimum wage. labour-intensive infrastructure-development It also aims to empower rural women initiatives that provide cash or food-based by promoting their participation in the payments in exchange for work. Such workforce through a quota: at least one- programmes have a number of advantages: third of all workers who have registered and they provide income transfers to the poor requested work under the scheme in each and are often designed to smooth income state must be women. Moreover, the Act during “slack” or “hungry” periods of the stipulates the payment of equal wages for year; they address infrastructure shortages men and women. Women’s status appears (rural roads, irrigation, water-harvesting to be strengthened when they are employed facilities, tree plantations, facilities for through the programme, particularly schools and health clinics); they are typically when they have access to income through self-targeting, in view of the relatively low their own bank accounts. NREGA’s design benefit levels and heavy physical labour incorporates the provision of crèche facilities, requirements (Subbarao, 2003), and thus intended as a means of enhancing women’s entail lower administrative costs than many participation, but the provision of child-care other safety-net measures. They are also facilities remains a serious implementation politically popular owing to the requirement challenge (Jandu, 2008; Holmes and Jones, that beneficiaries must work (Bloom, 2009), 2010). whereas generating support for direct cash transfers, particularly from middle- Strengthen women’s rights and voice class voters, can be more challenging (e.g. The lack of voice suffered by women, Behrman, 2007). especially in rural communities, is both The Ethiopian Productive Safety Net cause and consequence of the gender Programme was launched in 2005 as differences observed in rural labour markets.
  • 63. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 51 Institutional changes can help achieve decent work opportunities and economic Closing the financial services gap21 and social empowerment through labour markets and at the same time reduce Women’s access to financial services is gender inequalities in the context of conditioned by their legal, social and informal employment in agriculture. Public economic position within the community policies and legislation can influence public and household. Some of the interventions attitudes and the values that underlie required to close the gender gap in access gender inequalities. Government legislation to financial services are similar to those is essential for guaranteeing equitable needed for other asset categories. For employment conditions that protect workers example, giving women equal rights to in both formal and casual employment, enter into financial contracts is a crucial first the latter being of particular relevance to step in countries where legal and customary women. For example, governments can restrictions prevent women from opening support the organization of women in savings accounts, taking loans or buying informal jobs. At the same time, collective insurance policies in their own right. bargaining and voluntary standards can be Microfinance programmes have been important, in conjunction with more formal highly effective in overcoming the barriers legislation. Rural producer organizations faced by women in accessing formal and workers’ unions can play a vital role credit markets, as discussed in Chapter 3. in negotiating fairer and safer conditions Considerations for improving women’s access of employment, including better product to financial services are considered below. prices and wages, and in promoting gender equity and decent employment for men and Promote financial literacy women. Financial institutions, governments and NGOs Nevertheless, prevailing vertical and should offer financial literacy training to horizontal institutional arrangements (i.e. ensure that women can compare products producer organizations, cooperatives, and make decisions based on a clear workers’ unions, outgrower schemes) are understanding of the characteristics and generally controlled and managed by conditions of the products available (Mayoux men. There is thus a need for effective and Hartl, 2009). Such efforts could involve empowerment of women among the steps such as disseminating information and membership and leadership positions promotion materials in places or through in these organizations to ensure that channels that women can access, simplifying rural women have a stronger voice and application procedures and adapting them decision-making power.20 At the same to women’s literacy and numeracy levels, time, it is necessary to promote gender and simplifying insurance contracts and sensitivity within representative bodies communicating their conditions using through the training of men and women language and examples that less-literate representatives, as this does not derive women can easily understand. automatically from women’s participation. Women representatives do not always have Design products that meet the needs of the capacity to address issues in a gender- women sensitive way, especially when gender roles The past few years have seen noticeable are perceived as rigid or if there exists strong progress in extending insurance products opposition or conflict with men’s interest. to small producers and to rural areas. Crop Gender sensitivity training is also relevant for staff in institutions that work with women and implement gender-focused policies. 21 The material in this section is based on Fletschner and Kenney (2010). Important studies in this field include Berger (1989), Goetz and Gupta (1996), Pitt and Khandker (1998), Hashemi, Schuler and Riley (1996), Baydas, Meyer and Alfred (1994), Fletschner (2009), Fletschner and Carter (2008), Ashraf, Karlan and Yin (2010, Pitt, Khandker and 20 Additional information on women’s parliamentary Cartwright (2006), Holvoet (2004), Hazarika and Guha- representation is available at the website of the Inter- Khasnobis (2008), Besley (1995), Boucher, Carter and Parliamentary Union website (www.ipu.org). Guirkinger (2008) and World Bank (2007a).
  • 64. 52 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 insurance and livestock insurance, for into a major income shock for resource-poor instance, are increasingly being offered as households, and women may be particularly safety nets to farmers. Generally, however, vulnerable because they are more likely to be such products are designed without due assigned the role of caregiver. Illness in the attention to gender differences, and the family thus reduces women’s ability to engage degree to which women access them is in income-generating activities and weakens unclear. A notable exception to this pattern their ability to influence family decisions. is the approach taken by BASIX, a large Life events such as birth, death, marriage microfinance institution in India that offers and other cultural ceremonies also constitute weather insurance to women’s self-help shocks to rural households. Most micro- group members in drought-prone areas insurance plans described here cover (Fletschner and Kenney, 2010). pregnancy and birth-related expenses. Some A number of multilateral financial offer life and funeral insurance (Sriram, 2005; institutions and NGOs offer health insurance Mgobo, 2008), but informal safety nets, such to women (Table 2). Illness can translate as burial societies, remain important sources TABLE 2 Selected examples of health insurance products targeted towards women Provider Beneficiaries Details and country Bangladesh Rural Originally BRAC members Year started: 2001 Advancement Committee only; since 2007 open to all Members: 10 000 (as of 2004) (Matin, Imam and (BRAC) community members (poor Ahmed, 2005) Bangladesh rural women are policy- Results: 55 percent did not renew after first year; holders) poorer households less likely to know about programme and better-off households more likely to enrol; some clients found it difficult to pay annual premium; others who did not use services but enrolled found it to be a “waste” (ibid.) SKS SKS borrowers, who are Year started: 2007, expanded in 2009 to cover Bangladesh primarily women (spouse and spouses (usually husbands) up to two children covered) Members: 210 000 (as of 2008); required for all new borrowers or renewing borrowers (as of 2007) (Chen, Comfort and Bau, 2008) Results: Women aged 16–30 are heaviest users (ibid.) Self Employed Women’s SEWA members and non- Year started: 1992 Association (SEWA) members (women are policy- Members: 110 000 (as of 2003), two-thirds from India holders) rural areas (Ranson et al., 2006) Results: Found to reduce clients’ vulnerability to shocks overall, but slow processing costly to clients; initially coverage was mandatory for all borrowers, but once it became voluntary, 80 percent dropped coverage (McCord, 2001) SPANDANA Borrowers (compulsory, as Year started: 2003 (Sriram, 2005) India part of loan product) Members: 84 000, including spouses (as of 2004) (Sriram, 2005; CGAP, 2004) (CGAP, 2004). In 2007, 96.5 percent of borrowers were women (Mix Market, 2010) Port Sudan Association Women NGO members Year started: 2007 (Mayoux and Hartl, 2009) for Small Enterprise (individual low-cost access to Number of members: unknown Development (PASED) state health insurance) / Learning for (Mayoux and Hartl, 2009) Empowerment Against Poverty (LEAP) Sudan Kenya Women Finance Medium and low-income Year started: 2008 Trust Limited (KWFT) women, with option to cover Members: unknown, potentially 100 000 (total Kenya family members KWFT members) (Mgobo, 2008) Zurich Financial Services WWB affiliates (women Year started: 2009 and Women’s World member MFIs) Members: not yet known, but WWB network has Banking (WWB) 21 million members (WWB, 2010) (Global)
  • 65. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 53 of income-smoothing for rural households, reducing the need to travel long distances, especially for women, who may face the loss allowing them to sidestep social constraints of all assets upon a husband’s death (Dercon that restrict women’s mobility or the people et al., 2007; Mapetla, Matobo and Setoi, with whom they can interact (Duncombe 2007). and Boateng, 2009). In another example, a bank in Malawi that hosts small-scale savings Promote a women-friendly and has introduced innovations that give women empowering culture greater control over their income, such as Lenders and other financial institutions the use of a biometric card that allows only should promote a gender-sensitive culture the card holder to withdraw money from the throughout their organization (World account and the facility to open an account Bank, FAO and IFAD, 2009). Women should without an identity card, which many people be consulted and included in discussions, in rural areas do not possess. The bank has decision-making, planning and provision of successfully attracted large numbers of services. Marketing strategies, promotion women to open bank accounts (Cheston 2007, and service delivery should be gender- cited in Quisumbing and Pandolfelli, 2010). sensitive. Bringing men into projects and Financial institutions in countries such as groups can have positive effects on gender Brazil, India, Kenya, the Philippines and South relations and improve the success of the Africa have been able to reach rural customers project, but also risks losing the focus on at a lower cost by handling transactions women (Armendáriz and Roome, 2008). through post offices, petrol stations and A large body of evidence shows that stores, and many telecommunication service lending to women helps households diversify providers allow their customers to make and raise incomes and is associated with payments or transfer funds (World Bank, other benefits such as increased livelihood 2007a). These more accessible outlets can be diversification, greater labour market particularly beneficial for rural women who participation, more education and better have difficulty travelling to central business health. It does not necessarily empower locations. women, however, if they do not control the assets that are built or increased (Garikipati, 2008). Closing the gap in social capital Products designed to strengthen women’s through women’s groups position include the Grameen Bank’s loans for purchasing land or houses requiring Building women’s social capital can be that they be registered in women’s names an effective way to improve information and the loans offered by Credit and Savings exchange and resource distribution, to pool Household Enterprise in India for parents to risks and to ensure that women’s voices buy assets for their daughters, enabling them are heard in decision-making at all levels. to generate income, delay their marriage Community-based organizations, including and have assets they can take with them women’s groups, can be an effective means when they marry (Mayoux and Hartl, 2009). of generating social capital. Functioning as Along similar lines, a host of products have production cooperatives, savings associations been designed to benefit other women in and marketing groups, women’s groups the community indirectly (Mayoux and Hartl, can promote production and help women 2009): for instance, loans for businesses that maintain control over the additional income employ women, or for businesses that offer they earn, as has been demonstrated by services such as child care that benefit other a project based around polyculture fish women. production in Bangladesh. As the project proved successful in providing additional Use technology and innovative delivery incomes, the position of women within channels the household and community was also Technological innovations such as prepaid strengthened (Naved, 2000). cards and mobile phone plans to make loan Achieving scale through pooling resources payments and transfer cash make it easier can help women overcome some of the for women to gain access to capital by constraints faced by individual farmers.
  • 66. 54 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 In Kenya, women farmers pooled their and Jiggins, 2002). Women-only groups can land parcels and organized themselves to be an effective stepping stone to graduating establish savings associations and to deal into mixed-sex organizations or joining with stockists and traders. In this way, they established groups. were able to solve problems experienced Self-help groups have also proved to be in acquiring access to land, credit and an effective method for connecting women information (Spring, 2000). An impressive with financial institutions. Such groups may example of achieving scale is the Self operate at the village level and typically Employed Women’s Association (SEWA), require their members to meet regularly. which was founded in 1972 in Ahmedabad, Savings are collected from each member and India. This started as a small membership either deposited in rural banks or loaned organization for poor women working in to other group members. After a group has the informal sector. Today, it has more than demonstrated its capacity to repay loans, one million members in 14 districts across rural banks typically leverage the group’s India and aims at organizing groups with savings and provide additional capital that regard to services, access to markets and group members may use for agricultural fair treatment. Its largest cooperative is purposes (World Bank, FAO and IFAD, 2009). the SEWA Bank, which in 2007–08 had over There is evidence that working through 300 000 accounts with about US$16.6 million groups can help women retain control over in deposits (see Box 10). Established the loans they receive and enhance the associations and networks are not always returns to investments in women-managed accessible to women, as demonstrated by enterprises (Garikipati, 2008). another example, from southwest China. While groups can be an important way Here women found it difficult to access the of increasing women’s voice, there can male-dominated system of networks relating sometimes be an over-reliance on this to the formal plant-breeding system (Song mechanism. Women’s groups, like any BOX 10 India’s Self Employed Women’s Association (SEWA) The main goal of the Self Employed leaders. The low literacy levels of female Women’s Association (SEWA) is to participants are a major challenge to organize women to achieve full effective training delivery. SEWA also employment and self-reliance. In order to offers functional literacy training that achieve this, SEWA sets up small self-help is group-based and facilitated by a local groups that meet monthly in members’ trainer from the community. The training fields, homes or community rooms. focuses on reading skills and is designed Farmers choose to join these groups to around women’s specific needs. share mutual interests and concerns and SEWA’s village resource centres help to solve their problems collectively. For farmers, through the self-help groups, example, in the Sabarkantha district of to identify the potential benefits Gujarat State, SEWA supported small-scale of new technologies, evaluate their women farmers in creating a federation, appropriateness and participate in the Sabarkantha Women Farmer’s technology development processes. The Association, and conducted a watershed resource centres also provide farmers with conservation campaign in seven villages. good-quality inputs, market information SEWA’s facilitation approach includes and technical advice. SEWA’s cooperatives capacity building provided by professional are authorized seed distributors of the organizations. These organizations Gujarat State Seed Corporation and train SEWA members in managerial and provide timely and reasonably priced leadership skills, providing training for quality seeds (up to 20 percent below self-organization and collective action local market prices). The village resource to assist members in becoming confident centres communicate current output
  • 67. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 55 collective action process, face challenges clearly the specific issue they are trying to and costs. Membership fees may exclude address in group formation, and that using resource-poor women from joining, and existing, sometimes informal, groups and membership criteria such as land ownership networks has proved more successful than would bar landless women from becoming initiating them from scratch. members. Timing and length of meetings Mixed-sex groups can be more effective may interfere with women’s daily tasks. where joint action is required, such as in Building trust within newly formed groups natural resource management (Pandolfelli, can take a significant amount of time. Meinzen-Dick and Dohrn, 2008). In order for Women may also not be interested in women to participate actively in mixed-sex joining a group because the group does not groups, the groups must address women’s address their main concerns. Quisumbing problems and should be set up to allow the and Pandolfelli (2008) report results from a participation of more than one member of a project in the Philippines that encouraged household, if required (Meinzen-Dick et al., women to monitor a lake to assess whether 2010). Mixed groups should also allow for or not soil conservation techniques reduced women’s voices to be heard. A case study silting. Women’s participation was low, on Ethiopia found that meetings with only however, because their main interest was in women or with an equal number of men health issues. When the project started to and women increased women’s willingness emphasize the relationship between health to voice their opinion (German and Taye and water quality, women’s participation 2008). The specifics of group mechanisms, increased. Understanding the motivations such as the management of funds and for joining a group is therefore essential in sharing of benefits, and the share of women ensuring group sustainability (Pandolfelli, in leadership positions, will also play a Meinzen-Dick and Dohrn, 2008). Policy- significant role in encouraging women to makers and practitioners need to understand participate. prices to female leaders in each village well as their communication facilities such cluster through regular SMS messages, as the SEWA radio station. The SEWA thereby enabling the self-help groups approach is accountable and inclusive to bargain for better prices for their owing to its grassroots foundations and produce. the effectiveness of service provision Among the SEWA organizations that through self-help groups. SEWA is enable market access for small-scale also powerful because of its internal farmers, the Rural Distribution Network cohesiveness and its linkages with external (RUDI) plays a special role. RUDI acts as a partners such as government departments, link between farmers and consumers by universities, research and development making regularly used goods available agencies, NGOs and private companies. to villagers. Grains, spices and salt The 2 140 SEWA self-help groups from various districts are transported often radically improve women’s lives by to a processing centre and dispatched increasing their income and food security to selling centres. In this way, RUDI and by enabling them to seize new provides an outlet to farmer groups and opportunities. For example, the creation employment to saleswomen. of the Sabarkantha Women Farmer’s SEWA’s approach is particularly Cooperative enabled women farmers to successful because it is an integrated reclaim 3 000 hectares of ravine lands in process. Self-help groups and SEWA are 73 villages. Incomes increased from an closely linked through SEWA institutions average of 5 000 Indian rupees (about such as their microfinance and insurance US$ 112 ) to as much as 15 000 Indian agencies and their training facilities, as rupees a year.
  • 68. 56 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 The ability to organize mixed-sex groups could be made much less onerous and time- will depend on the gender segregation consuming through the adoption of simple within a community. In communities with a technologies. high level of gender segregation, single-sex Water is of particular importance to groups may lead to more desirable outcomes rural households because it is necessary for women (Pandolfelli, Meinzen-Dick and for agricultural and household chores, Dohrn, 2008). Sometimes, however, excluding but men and women often have different men can generate unnecessary obstacles. priorities with regard to water use. Women A project introducing the new livelihood are frequently responsible for collecting all strategy of mud-crab production to supply water used domestically, i.e. drinking water, hotels in Unguja Island, United Republic of sanitation and health. The introduction of Tanzania, excluded men and the resultant water sources in villages can significantly anger among the men added transaction and reduce the time spent by women and girls input costs as women had to rely on a small fetching water (IFAD, 2007). For example, number of male fishers for seedstock and the construction and rehabilitation of water feedstuff (Coles and Mitchell, 2010). Projects sources in six rural provinces of Morocco that intervene within the local socio-cultural reduced the time that women and young dynamics should avoid “default” options girls spent fetching water by 50–90 percent. and, instead, base their interventions on the Primary school attendance for girls in these specific context and the underlying problem. provinces rose by 20 percent over a period of four years, which was partly attributed to the fact that girls spent less time fetching water Closing the technology gap (World Bank, 2003). Water projects that meet multiple Closing the gap in women’s access to a livelihood objectives and take gender issues broad range of technologies could help free properly into account are more likely to be their time for more productive activities, sustainable (Quisumbing and Pandolfelli, enhancing their agricultural productivity, 2010). In Manzvire village, Zimbabwe, for improving the market returns they receive example, a borehole rehabilitation project and empowering them to make choices that involved men and women in the decision- are better for themselves and their families. making process regarding the appropriate Closing the technology gap requires that technology and sites for new water points, the necessary technologies exist to meet and women were trained in maintaining the the priority needs of female farmers, that new water sources. Their active involvement women are aware of their usefulness, and provided women with a strong sense of that they have the means to acquire them. ownership for the sources; for example, they established saving schemes that provided Develop technologies and environments funds to buy spare parts. One of the project’s that address women’s needs results was that four times more boreholes Previous chapters documented that rural than targeted were rehabilitated (Katsi, women work very long days balancing a 2006). variety of tasks related to crop and livestock Firewood collection for cooking purposes production, wage employment, child care can also occupy a large share of women’s and additional household obligations. time and is – quite literally – a heavy burden. The latter, such as food preparation and Women in rural Senegal, for example, collecting firewood and water, occupy a walk several kilometres a day carrying large amount of women’s time and limit loads of over 20 kg of wood (Seck, 2007). women’s participation in more productive Deforestation and unfavourable weather activities. Studies from Kenya, Uganda events, such as drought, can increase and the United Republic of Tanzania, for the time spent on firewood collection. example, show that children and women Fuel-efficient stoves can reduce firewood in rural areas fetch water from the main requirements by 40–60 percent (FAO, 2006b), water source on average four times per day in addition to reducing indoor pollution and require about 25 minutes for each trip and the time required for cooking. Locally (Thompson et al., 2001). Many of these tasks manufactured stoves can also provide
  • 69. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 57 income-earning opportunities for rural access to them. Conducting baseline surveys artisans. In western Kenya, for example, of households and communities before new the introduction of the Upesi stove led to technologies are introduced may help predict considerable reductions in smoke levels. how men and women will be affected Women who used the stove reported time- by them (Quisumbing and Pandolfelli, savings of about ten hours per month. 2010). Greater involvement of women in The stove saves up to 40 percent of fuel agricultural research and higher education compared with traditional three-stone could also enhance the development of fires and has a lifespan of about four female-friendly technology. years. Upesi stoves are produced by local Improved crops with higher yields and women’s groups, generating income-earning better adapted to pests and diseases can opportunities for rural women (Okello, also be labour-saving, by reducing the time 2005). Woodlots, agroforestry and improved for cropping operations. Certain crops, for fallows can further reduce the time spent in example cassava and other root and tuber collecting firewood by bringing the sources crops, have lower labour requirements of firewood closer to the home. These and allow for more flexibility in cropping measures require secure tenure as well as operations. Varieties that are harvested labour inputs and investments for which in seasons with low labour requirements benefits will only be realized after a number can ease labour bottlenecks. Integrated of years (FAO, 2006b). pest management techniques can decrease Appropriate farm tools for women can labour requirements and costs for pesticide also reduce drudgery and time spent in the application, reduce farmer exposure to field. Farm tools that are predominantly hazardous chemicals and increase yields. used in operations dominated by women, Conservation agriculture, or no-tillage for example weeding or post-harvest systems, decreases the labour needed for activities, are often not gender-specific. In land preparation and weeding, because the fact, technology developers often think of field is covered with cover crops and seeding technologies as being gender-neutral, but on is done directly without preparing the average women tend to be of lower weight seedbed (FAO, 2006b). Biological nitrogen- and height compared with men and may not fixation technologies to improve soil fertility, have equal muscular strength (Singh, Puna Ji such as agroforestry innovations or grain Gite and Agarwal, 2006). Improved farming legumes, can raise productivity and save tools can facilitate seed-bed preparation, labour. planting, weeding and harvesting activities. For example, a case study in Burkina Faso, Improve extension services Senegal, Uganda, Zambia and Zimbabwe Extension services are important for showed that long-handle hoes could ease the diffusing technology and good practices, burden of the work for women compared but reaching female farmers requires careful with traditional short-handle hoes, but consideration. In some contexts, but not all, they were not acceptable in some of the it is culturally more acceptable for female countries because standing up was associated farmers to interact with female extension with laziness (IFAD/FAO/FARMESA, 1998). agents. Whether they are male or female, Another study from India demonstrated that extension agents must be sensitive to the women who used a groundnut decorticator needs and constraints faced by their female were able to decorticate about 14 times clients. Extension services for women must more groundnuts and used significantly less consider all the roles of women; women’s physical effort than women who decorticated needs as farmers are often neglected in groundnuts by hand. When preparing land favour of programmes aimed at household with a new hand tool designed for making responsibilities. ridges for vegetable crops, women were able Hiring female extension agents can be to double the number of rows finished in an effective means of reaching female one hour (Singh, Puna Ji Gite and Agarwal, farmers. The United Republic of Tanzania, 2006). Thus, attention should be paid to for example, raised the share of female developing appropriate, context-specific extension agents to 30 percent in the technologies as well as enhancing women’s mid-1990s, because many female farmers
  • 70. 58 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 indicated that “they felt freer to discuss 23 percent higher increases in income from problems with them ... and their time livestock production than participants from preferences were better met” (Due, male-headed households and were able to Magayane and Temu, 1997). This preference nearly double per capita agricultural income. is not universal, however, so in many cases FFS were easily accessible to women as well properly trained male extension agents may as to poor farmers and farmers with low be able to provide equally effective services. literacy levels. Farmers particularly valued Male extension agents must be sensitized the participatory learning approach and the to the realities of rural women and the ability to do practical experiments using new quality of information provided to women technologies in the field (Davis et al., 2009). improved. This requires careful and location- When targeting female participation in specific analysis of their situation. Cultural the FFS, time constraints play a significant barriers could be overcome by organizing role. A case study of FFS for integrated pest women in groups and possibly providing management in rice in Sri Lanka showed that separate training for male and female they can take up to 15 half-day meetings in a farmers. Extension systems will also have single season (Tripp, Wijeratne and Piyadasa, to be more innovative and flexible to 2005). Crop preferences or crop operations account for time and mobility constraints. relevant to women farmers also determine Indeed, women farmers tend to be less the extent to which women participate. A mobile than their male counterparts owing participatory potato research initiative in to time constraints, restricted access to Peru attracted only about 12 percent female transportation and potential social and participation because women thought cultural obstacles that keep them from of potato as a “male” crop. However, travelling outside their village boundaries. participation was as high as 60 percent in Women also often have seasonal workloads sessions dealing with planting, harvesting that can conflict with the timing of extension and evaluating potato clones because these training programmes. tasks were perceived as “female” (Buck, The Government of Ethiopia has 2001; Vasquez-Caicedo et al., 2001). endeavoured to render its extension services FFS are sometimes criticized as being more gender-responsive by mandating its financially unsustainable because they national and regional Bureaus of Agriculture require high initial investments and to introduce extension services closely linked significant recurrent costs. Comparisons to women’s activities, to encourage women show that costs vary widely by country and to participate in every programme and to crop, and that costs per farmer decline as assist women in obtaining better access to project managers learn to use local training agricultural inputs (Buchy and Basaznew, materials, replace international experts 2005). Women’s involvement in farmer-to- with local staff, and increase the number farmer training and extension has also had of participants (van den Berg and Jiggins, positive results in Uganda (Box 11). 2007). In order to increase the impact of FFS on women and to ensure their sustainability, Scale up farmer field schools it is important to train women farmers Farmer field schools (FFS) have proved to in effectively communicating learned be a participatory and effective way of experiences. This will enable them to become empowering and transferring knowledge facilitators in other FFS or to communicate to women farmers. For example, women with non-participating farmers. in Kenya, Uganda and the United Republic of Tanzania who participated in FFS were more likely to adopt major technologies, Key messages including improved crop varieties, livestock management and pest control techniques. • Gender gaps can be closed across a wide In all three countries, women made up, on range of agricultural inputs, assets and average, 50 percent of all FFS participants services. Many steps are required by and they benefited significantly from their many different actors – governments, participation. For example, participants civil society, the private sector and from female-headed households achieved individuals – but the basic principles are
  • 71. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 59 BOX 11 Women in a sustainable rural livelihoods programme in Uganda1 Women feature prominently in a trainers are women: about 58 percent sustainable rural livelihoods (SRL) of community-based rural development programme established in 2004 in eastern extension workers, 75 percent of Uganda’s Kamuli District. The primary community nutrition and health workers, goals of the programme are to improve 76 percent of committee members and food security, nutrition and health at 71 percent of executive committee the household and community levels. members. Related goals are increased sources and In response to the training and support levels of income, resilience to stresses and that they receive, the rural development shocks, and the sustainable management extension and community nutrition and of natural resources. The SRL is a health workers provide training and collaborative programme of Iowa State outreach to farmer group members and University’s Center for Sustainable Rural others in their communities and well Livelihoods, Makerere University’s Faculty beyond. More than 2 000 other households of Agriculture and VEDCO (Volunteer have benefited from training and outreach Efforts for Development Concerns), a services provided by these workers. Ugandan NGO. As a result of their participation in this The programme employs a farmer-to- programme, women’s human capital has farmer training and extension approach to been enhanced through training and demonstrate and disseminate information through experience gained in developing on key management practices, for leadership skills, improved nutrition and example: planting banana or cassava health, and community-wide respect in ways that ensure productivity and for their role as sources of valuable control diseases, enhancing soil fertility knowledge. In terms of social capital, they through composting with manure, are integrally involved in farm groups and growing and utilizing nutrient-dense emerging marketing associations. Another crops such as amaranth grain and Vitamin key result has been a significant increase in A-rich sweet potatoes. It also emphasizes household food security. the establishment of multiplication Innovations made through this three- gardens and seed nurseries, post-harvest way partnership in Kamuli District are management and storage, improving now being mainstreamed in VEDCO’s livestock breeding and feeding, integrating rural development support programme nutrition and health with agriculture, farm activities in nine other districts – for 25 000 enterprise development, marketing, and smallholder farmers. strengthening farmer groups. Groups were formed following community meetings and were often based on existing self-help groups such as 1 Prepared by Robert Mazur, Professor of Sociology and Associate Director for Socioeconomic savings clubs. A large proportion of the Development in the Center for Sustainable Rural 1 200 farm group members, leaders and Livelihoods, Iowa State University, USA. the same across the board: eliminate government officials and community discrimination under the law, make leaders and holding them accountable gender-aware policy and programming for upholding the law and empowering decisions, and give women greater voice women to ensure that they are aware of in decision-making at all levels. their rights and able to claim them. • Closing the gap in access to land and • Women’s participation in rural labour other agricultural assets requires, markets requires freeing women’s time among other things, reforming laws through labour-saving technologies to guarantee equal rights, educating and the provision of public services,
  • 72. 60 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 raising women’s human capital through research and technology development education, eliminating discriminatory programmes, the provision of gender- employment practices, and capitalizing sensitive extension services and the on public works programmes. scaling up of FFS. • Closing the gap in financial services • Women’s groups and other forms of requires legal and institutional reforms collective action can be an effective to meet the needs and constraints of means of building social capital and women and efforts to enhance their addressing gender gaps in other areas financial literacy. Innovative delivery as well, through reducing transactions channels and social networks can reduce costs, pooling risks, developing skills and costs and make financial services more building confidence. Women’s groups readily available to rural women. can be a stepping stone to closing the • Improving women’s access to agricultural gender gap in participation in other civil technologies can be facilitated society organizations and government through participatory gender-inclusive bodies.
  • 73. W O M E N I N A G R I C U L T U R E : C losi n g t h e ge n de r g a p fo r de v elop m e n t 61 6. Closing the gender gap for development Evidence from an extensive body of implementing provisions and policies social and economic research surveyed on gender equality. Governments and in this report confirms the contributions civil society must work together to women make to the agriculture sector ensure that women are aware of their and rural enterprises, the gender-specific rights and have the support of their constraints they face in accessing resources governments, communities and families and opportunities, the potential benefits in claiming their rights. for the sector and society that could be • Strengthen rural institutions and make achieved by reducing those constraints, and them gender-aware. Strong, effective lessons learned from policies, programmes and inclusive rural institutions are and interventions aimed at closing the essential for poverty reduction, economic gender gap in agriculture. The conclusions development and the empowerment are clear: (i) gender equality is good for of small producers and the rural poor, agriculture, food security and society; and particularly women. Efforts are required (ii) governments, civil society, the private to ensure that women and men are sector and individuals, working together, can equally served by rural institutions support gender equality in agriculture and such as producers’ organizations, rural areas. labour unions, trade groups, and other Enabling women to achieve their membership-based organizations. Other productive potential requires many of the public and private service providers that same reforms that are necessary to address operate in rural areas, such as extension constraints facing small-scale farmers and services, animal health services and rural people in general, but additional care microfinance organizations, should must be taken to ensure that women’s voices consider the specific needs of men and are heard in the design and implementation women to ensure that their activities are of policies and interventions. No simple gender-aware. Women’s groups have an “blueprint” exists for achieving gender important role to play, but other rural equality in agriculture, but some principles institutions must also be accessible to are universal and many lessons can women and responsive to their needs. be learned about best practices. Basic • Free women for more rewarding and principles for achieving gender equality and productive activities. The most valuable empowering women in agriculture include asset most poor people have is their own the following: labour, but many women are compelled • Eliminate discrimination against women to spend too much of their time in under the law. Governments have a drudgery: fetching water, carrying fundamental responsibility to ensure wood, and processing food by hand. that their laws and policies guarantee Such work has to be done because water equal rights for men and women to pumps, modern fuel sources and grain control assets such as land and to receive mills are missing. Investments in basic services such as education, extension infrastructure for essential public services and credit. Governments also have a can liberate women from this drudgery responsibility to ensure that institutions and free them for more rewarding and and officials at all levels are fully productive work. supportive of the realization of equality • Build the human capital of women under the law. Officials must understand and girls. No single intervention can by the law and be held accountable for itself address the multiple challenges
  • 74. 62 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 enumerated in this report, but building used to ensure that the resulting data the human capital of women and girls accurately highlight gender interactions is fundamental. General education and and inequalities in the agriculture the ongoing transfer of information and sector. More detailed time-use surveys practical skills will broaden the range of would lead to greater understanding choices women can make and give them of women’s contributions to household more influence within their households production and welfare as well as to and communities. Building women’s their time constraints. The quantity and human capital makes them better quality of sex-disaggregated data for farmers, more productive workers, better policy-making can be increased through mothers and stronger citizens. the integration of agricultural censuses • Bundle interventions. Some assets are and surveys and the retabulation of complementary and the constraints existing census data. Gender differences women face are often mutually and their implications may be more reinforcing. Interventions therefore visible when sex-disaggregated data are should be appropriately bundled and collected, analysed and presented at sequenced and should consider women subnational levels and by age groups. within their broader social contexts. • Make gender-aware agricultural policy Relaxing one constraint may be helpful, decisions. Virtually any agricultural but others may soon become binding, so policy related to natural resources, it is often necessary to address multiple technology, infrastructure or markets constraints. What is more, it is impossible will affect men and women differently to separate women’s economic activities because they play different roles from their household and community and experience different constraints roles and responsibilities. The gender- and opportunities in the sector. related constraints women face due Good agricultural policy requires an to power relations within the family understanding of the gender dimensions and community may affect their ability at stake. Because some agricultural to engage in economic activities and and gender issues are location-specific, retain control over the assets they these may best be addressed through obtain. Bringing men into the process location-specific assessments and will help ensure that progress towards tailored policies and programmes. gender equality is broadly beneficial and Because interventions may have gender- sustainable. impacts that are difficult to predict, • Improve the collection and analysis of policies and programmes should include sex-disaggregated data.22 Understanding the collection of baseline data and of many gender issues in agriculture rigorous monitoring and evaluation, – including crop, livestock, fisheries and practitioners should be prepared to and forestry sectors – is hindered by reformulate their activities in response the lack of sex-disaggregated data, to unforeseen developments. Making and inadequate analysis of the data women’s voices heard at all levels in that exist. Agricultural censuses should decision-making is crucial in this regard. focus more attention on areas in which women are relatively more active and collect sex-disaggregated data on ownership of, access to and control over productive resources such as land, water, equipment, inputs, information and credit. They should avoid gender biases in the concepts and definitions 22 FAO has developed the Agri-Gender Statistics Toolkit FAO, 2010i), providing technical guidance to support the enhanced production and use of sex-disaggregated agricultural data.
  • 75. Part II World food and agriculture in review
  • 77. W o r ld food a n d a g r icul t u r e i n r e v iew 65 World food and agriculture in review From 2007 to 2009, a food price crisis followed by the financial crisis and global Trends in undernourishment24 economic recession pushed the number of With the improved prospects for the global hungry and undernourished people in the economy and lower food commodity world to unprecedented levels, reaching prices, FAO projects that the number of a peak in 2009 of more than 1 billion.23 In undernourished people in the world will the first half of 2010, world agricultural decline in 2010 to 925 million people, from commodity markets appeared to enter the estimated 2009 peak of 1.023 billion calmer times. Prices of food and agricultural (Figure 17). Despite this welcome commodities remained high, but had reduction in world hunger, the number of nevertheless declined from the peaks of undernourished remains unacceptably high, 2008, and the world economy was emerging representing the second-highest number from recession. since FAO’s records began.25 However, there are growing concerns The decline in 2010 constitutes a reversal about high market volatility. These were of the constant upward trend observed reinforced from June through October since 1995–97. Indeed, after a steady, albeit 2010, when cereal prices – particularly slow, decline from 1970–71 to 1995–97, the those of wheat and maize – increased as following years saw a gradual increase in drought in the Russian Federation and high the number of undernourished people in temperatures and excess rain in the United the world. The upward trend accelerated States of America reduced supplies. During sharply in 2008 during the food price crisis. the food price crisis, many governments The number of undernourished spiked in took a number of uncoordinated policy 2009 as a result of the financial crisis and actions intended to ensure adequate the persistence of high food prices in the supplies on domestic markets, inter alia domestic markets of many countries in through export bans and other restrictions developing regions. on exports. Many of these actions, in fact, In spite of the increase in the absolute exacerbated price volatility on international number of undernourished people between markets. 1995–97 and 2009, the proportion of the This part of the report examines levels and population who are undernourished in the trends in global hunger in the context of developing world26 continued to decline, recent developments in agricultural markets albeit very slowly, even after 1995–97, before and the global economy. It reviews recent increasing in both 2008 and 2009 (Figure 18). trends in global production, consumption In 2010, 16 percent of the population in and trade of food and agricultural products developing countries were undernourished, and discusses price developments on down from 18 percent in 2009 but still well international and domestic food markets. above the target set by the Millennium The analysis focuses on increasing disquiet Development Goal 1C to halve to 10 percent over price volatility and the resilience of the proportion of undernourished between markets to price and economic fluctuations. 1990 and 2015. 23 This review of world food and agriculture is based on 24 A more detailed analysis of trends in global information available at the end of October 2010. More undernourishment and the impact of the crisis on global current information on agricultural markets and the food security can be found in FAO, 2010g. world food situation can be found at http://www.fao.org/ 25 FAO estimates date back to 1969–71. worldfoodsituation/wfs-home/en/?no_cache=1 and http:// 26 Countries in developing regions account for 98 percent www.fao.org/publications/sofi/en/ of the world’s undernourished population.
  • 78. 66 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 17 Number of undernourished people in the world, 1969–71 to 2010 Millions 1 050 2009 1 000 950 2008 2010 900 1969–71 1990–92 850 2000–02 1979–81 2005-07 800 1995–97 750 Notes: Figures for 2009 and 2010 are estimated by FAO with input from the United States Department of Agriculture, Economic Research Service. Full details of the methodology are provided in the technical notes available at www.fao.org/publication/SOFI/EN/. Source: FAO, 2010g. FIGURE 18 Proportion of population that is undernourished in developing regions, 1969–71 to 2010 Percentage 35 1969–71 30 25 1979–81 1990–92 20 2009 2000–02 2008 15 1995–97 2005–07 2010 10 5 0 Source: FAO, 2010g. Most of the world’s 925 million hungry is found in sub-Saharan Africa, where in people (62 percent of the total) live in 2005–07 (the latest period with complete Asia and the Pacific, the world’s most information by country) 30 percent of the populous region, followed by sub-Saharan total population were estimated to be Africa, home to 26 percent of the world’s undernourished, although large variations undernourished population (Figure 19). The occur among countries. While the prevalence highest prevalence of undernourishment of hunger is lower in Asia and the Pacific
  • 79. W o r ld food a n d a g r icul t u r e i n r e v iew 67 (16 percent), Latin America and the Although international food commodity Caribbean (9 percent) and the Near East and prices fell in 2009, they remained high North Africa (7 percent), it varies greatly relative to prior years, and data through to by subregion and by country within these October 2010 indicate an increase in the FPI regions. from 2009 to 2010. Moreover, high domestic prices have persisted in many countries, as Vulnerability of global food security the decline in international prices was slow to shocks in being transmitted to domestic markets. The events of the past few years have While food prices remained above their highlighted the vulnerability of global pre-crisis level, reduced incomes caused by food security to major shocks – both in the financial crisis had a detrimental effect the global agricultural markets and in the on access to food, leading to a further world economy. The food price crisis and sharp increase in global undernourishment the ensuing economic crisis reduced the levels. According to estimates of growth purchasing power of large segments of the in per capita GDP (approximated using population in many developing countries, International Monetary Fund [IMF] severely curtailing their access to food and estimates of growth in total GDP minus thus undermining their food security. population growth rates), the global GDP The rise in global undernourishment per capita contracted in 2009, with the numbers in 2008 was a result of the spike advanced economies affected more than in food prices from 2007 to 2008. From a the economies of the developing world historical perspective, the price developments (Figure 21). However, per capita GDP in this period are not unprecedented, with declined or stagnated in all developing markets exhibiting a comparable spike regions, with the exception of developing during the “world food crisis” of 1973–75 Asia – where per capita GDP growth (Figure 20). Even so, FAO’s Food Price Index slowed to 5.8 percent, compared with (FPI) declined in real terms (using the United more than 10 percent in 2007 (IMF, 2010a; States GDP deflator) over the period 1961– IMF, 2010b). The economic recession had a 2010. severe negative impact on export revenues, Since the early 2000s, however, the foreign direct investments and foreign downward trend appears to have been migrant remittances received by developing reversed, or at least interrupted, with food countries (FAO, 2009b). By 2010, the prices increasing significantly in real terms, burgeoning recovery of the world economy culminating in the price spike of 2007–08. and the significant increases in economic FIGURE 19 Number of undernourished people in 2010, by region (millions) 37 19 53 578 Asia and the Pacific 239 Sub-Saharan Africa Latin America and the Caribbean Near East and North Africa Developed regions Total: 925 million Source: FAO, 2010g.
  • 80. 68 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 20 FAO Food Price Index in real terms, 1961–2010 Index (1990 = 100) 400 350 300 250 200 150 100 50 0 1961 1968 1975 1982 1989 1996 2003 2010 Notes: Calculated using international prices for cereals, oilseeds, meats, dairy products and sugar. The FAO Food Price Index is calculated from 1990 to the present on a regular basis; in this figure it has been extended back to 1961 using proxy price information. The index measures movements in international prices and not necessarily domestic prices. The United States GDP deflator is used to express the Food Price Index in real rather than nominal terms. Source: Calculations by FAO. growth rates underpinned the reduction in global undernourishment numbers discussed Food production, above. consumption and trade In spite of the declining numbers in 2010, during the crises reflecting the resumption of economic Recent trends in global food growth and reduction in food prices, the production, consumption and trade two crises have drawn our attention to the According to data and estimates available acute vulnerability of poor countries and by mid-2010,27 growth in the global food populations to global shocks such as those production index (measured in constant experienced in the most recent years. In prices) slowed to about 0.6 percent in 2009, addition, localized shocks and emergencies following significant increases of 2.6 and have affected food security in specific 3.8 percent respectively in 2007 and 2008 – countries as well as at the subnational during the food price crisis (Figure 22, page level (see Box 12 for a discussion of food 72). At the same time, global agriculture emergencies in countries requiring external assistance). Mechanisms to protect the most 27 The indices of food production, consumption and trade vulnerable populations from the effects of in this section are based on data derived from FAO, Food Outlook, June 2010 (FAO, 2010k), updated to reflect such shocks are often woefully inadequate. production estimates in September 2010. Indices express Consequently, vulnerable households may production, consumption and trade in constant prices be forced to deal with shocks by selling and have been computed using international reference productive assets, which are very difficult to commodity prices averaged during 2004–06. Production indices are net of feed and seedstock. Consumption indices rebuild, thus extending and prolonging the are derived from estimates of food use. Commodities negative impacts of the crisis far beyond its covered include wheat, coarse grains, rice, oilseeds, immediate effect. vegetable oils, meat and dairy products.
  • 81. W o r ld food a n d a g r icul t u r e i n r e v iew 69 FIGURE 21 Average annual percentage change in GDP per capita at constant prices, 2005–2010 2005 World 2006 2007 Advanced economies 2008 2009 Emerging and 2010 developing economies Central and Eastern Europe Commonwealth of Independent States Developing Asia Near East and North Africa Sub-Saharan Africa Latin America and the Caribbean -8 -6 -4 -2 0 2 4 6 8 10 12 Notes: Figures from 2010 are projections based on data from the first three quarters of that year, incorporating the most recent estimates made in October. Source: Author’s calculations, using data from IMF, 2010a and IMF, 2010b. has been affected by other shocks, such over 2 percent per year (almost 1 percent as the drought in the Russian Federation in per capita terms), fell marginally in per during the summer of 2010, which caused capita terms during the economic recession the country’s wheat production and in 2009. Growth in trade had been around exports to fall dramatically. Growth of only the 4–6 percent range annually before the 0.8 percent is projected for 2010. Global food financial crisis; in 2009 it contracted and is consumption, which had been increasing at projected to remain negative in 2010.
  • 82. 70 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 Box 12 Food emergencies Food crises affecting individual countries assistance for food.1 Food crises can be shock and destabilize the food security triggered by a number of factors – natural or status of part of or the entire population human-induced. If the emergency is natural, (the newly food-insecure) and worsen it may be described as either sudden or slow- it for those who were already food- onset,2 and if it is human-induced it may be insecure prior to the emergency (the the result of socio-economic problems3 or chronically food-insecure). FAO’s Global war/conflict (see figure). Information and Early Warning System The total number of recorded on food and agriculture (GIEWS) emergencies in recent years is far higher monitors and disseminates information than in the 1980s. Since the mid-1980s, the on countries in crisis requiring external general trend has been towards an increase Emergencies (by type) in countries requiring assistance, 1981 to 2009 Number of countries 80 70 60 50 40 30 20 10 0 1981 1985 1989 1993 1997 2001 2005 2009 Human-induced / War Human-induced / Socio-economic Natural / Slow Natural / Sudden Note: Data on emergencies do not include events taking place in 2010. At the time of writing, floods in Pakistan amounted to the world’s largest humanitarian crisis ever, with up to 20 million people affected (about 18 percent of the country’s population) and 6 million people in need of food assistance. The crisis was far larger than both the tsunami of 2004 and the Haitian earthquake of early 2010 combined. Source: FAO. Food consumption per capita by the region was particularly hard hit by the region economic downturn. The most rapid growth in per capita Food consumption per capita has remained consumption of basic foods in recent years stagnant-to-falling in the developed regions has been recorded in Eastern Europe, of North America, Western Europe and followed by Latin America and the Oceania. In sub-Saharan Africa, it rose Caribbean, then Asia and the Near East and between 2000 and 2007, but is estimated North Africa (Figure 23, page 72). In these to have fallen somewhat on a per-capita regions, per capita consumption generally basis since then. In this context, however, it continued to rise even during the recession. is important to bear in mind that estimates An exception was Eastern Europe, which saw provided in this analysis do not include all a decline of some 2 percent in 2009, when food items; roots and tubers, for example,
  • 83. W o r ld food a n d a g r icul t u r e i n r e v iew 71 in the number of countries affected by have begun. Countries in protracted crisis emergencies. The number of human-induced face a particularly difficult situation. emergencies seems to have increased the According to The State of Food Insecurity most, with war/conflict accounting for most in the World 2010 (FAO, 2010g), 22 of them. Over the past decade and a half, the countries are currently considered to be in frequency of sudden-onset natural disasters a state of protracted crisis. Protracted crisis appears to have been on an upward trend. situations are characterized by recurrent From 1981 to 2009, the region with the natural disasters and/or conflict, longevity largest number of countries experiencing of food crises, breakdown of livelihoods emergencies was Africa, followed by Asia, and insufficient institutional capacity to Latin America and the Caribbean, Eastern react to the crisis. Such countries need Europe, Commonwealth of Independent to be considered as a special category States (CIS) and Oceania. The high incidence with special requirements in terms in Africa is explained in part by the relatively of interventions by the development large number of countries in the region community. (For a detailed discussion (44 are assessed by GIEWS), but also by of the special situation of countries in civil unrest occurring in many countries as protracted crisis, see FAO, 2010g.) well as numerous slow-onset disasters. The number of African countries experiencing emergencies has ranged from around 15 to 25 annually, with the exception of the late 1980s, when the number was closer to 10. Of the 23 countries considered in the Asian region, the number experiencing emergencies has increased from around 5 annually during the period 1981–2002 to 1 Some countries that have consistently funded around 10 from 2003 to 2009. The number their own response to emergencies rather than seeking assistance from the international of countries affected in Latin America and community are excluded from the information the Caribbean is relatively small but has collected and disseminated by GIEWS. fluctuated over the time period, whereas 2 Natural sudden emergencies include sudden onset disasters such as floods, cyclones, hurricanes, in Eastern Europe and the CIS it has been earthquakes, volcanoes, and locusts. Slowly decreasing. developing natural disasters such as drought, adverse weather, and transboundary pests and Just as the effects of economic shocks on diseases are classified as natural slow emergencies. hunger do not disappear entirely when prices 3 Examples of human-induced socio-economic emergencies are crises caused by commodity price recover and economic growth resumes, the collapses/spikes, loss of export markets, currency impacts of crises on food security may also problems, land tenure problems and health- persist long after relief and recovery efforts related crises. which are widely consumed in sub-Saharan production, including structural causes Africa, have not been included. and weather-related factors. Generally, production in industrialized countries and Food production by region the “BRIC” countries28 responded most to the The global production estimates for the high crop prices of 2007 and 2008. However, period 2006–10 presented in Figure 22 over the last decade the strongest production illustrate a global production response growth was achieved by the LDCs and the stimulated by high, then falling food prices. “rest of the world” (Figure 24, page 73). However, more detailed regional and The two geographic regions that national data underlying the aggregates experienced the strongest growth in food present more complex patterns, reflecting the impact of other influences on agricultural 28 Brazil, Russian Federation, India and China.
  • 84. 72 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 22 Annual growth in global food production, consumption and trade, 2006–2010 Percentage change 7 Production 6 Consumption 5 Trade 4 3 2 1 0 -1 2006 2007 2008 2009 2010 Note: Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates. Source: FAO. FIGURE 23 Indices of per capita food consumption by geographic region, 2000–10 Index (2004–06 = 100) 115 Northern America Latin America and 110 the Caribbean Western Europe 105 Eastern Europe Near East and 100 North Africa Sub-Saharan Africa 95 Asia Oceania and Japan 90 85 80 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Note: Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates.
  • 85. W o r ld food a n d a g r icul t u r e i n r e v iew 73 FIGURE 24 Indices of food production by economic group Index (2004–06 = 100) 120 World BRIC countries 115 OECD countries 110 LDCs Rest of the world 105 100 95 90 85 80 2000 2002 2004 2006 2008 2010 Note: Net of feed and seedstock. Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates. BRIC = Brazil, Russian Federation, India and China; LDCs = least-developed countries. Source: FAO. production over the last decade – Eastern Union (EU), but declined by around 2 percent Europe and Latin America and the Caribbean in 2009 as a result of lower prices and – had mixed experiences during the food unfavourable weather conditions. price and financial crises (Figure 25). The Eastern European countries, after recording Food exports by region bumper crops in 2008, were unable to sustain Food exports by nearly all regions, fell or potential growth in the subsequent years, and stagnated in 2009 during the economic the 2010 drought led to substantially reduced crisis (Figure 26). From 2000 to 2008, Eastern levels of crop production in the region. Europe saw cumulative export growth of Latin America and the Caribbean suffered around 350 percent; in 2008 it recorded a weather-related production shortfalls in particularly high level of grain production. 2008 but recovered in 2009 and 2010. In Asia, However, exports declined the following growth in food production remained strong year and even more significantly as a result throughout the last decade, generally in the of drought in 2010.29 Food exports from range of 2–4 percent per year, but recorded a Western Europe declined, possibly as a result slowdown in 2009 and 2010. of the rise in the value of the euro as well Production failed to grow in 2009 in sub- as of successive policy reforms, including Saharan Africa, which had seen growth in the reform of the EU Common Agricultural the range of 3–4 percent per year over the Policy. Strong export performances previous decade; it is expected to expand by countries in Latin America and the moderately in 2010. The region registering Caribbean, for which food exports nearly the slowest growth in food production doubled over the decade, have made this in recent years is Western Europe, where region an increasingly important supplier production in 2010 is projected to be of food to global markets. However, the only some 5 percent higher than in 2000. Production did increase in 2007 and 2008 29 The trade index values by region include trade within under the effect of high prices and reduced the region; this may affect conclusions about relative trade set-aside requirements in the European performance.
  • 86. 74 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 25 Indices of food production by region, 2000–10 Index (2004–06 = 100) 130 Northern America Latin America and the Caribbean 120 Western Europe Eastern Europe 110 Near East and North Africa 100 Sub-Saharan Africa Asia Oceania and Japan 90 80 70 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Note: Net of feed and seedstock. Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates. Source: FAO. region’s food exports stagnated in volume subsequent economic downturn translated terms during the food price crisis and during into a decline in import volumes in 2008 and the economic recession. Export volumes stagnating levels in 2009 and 2010. During from North America grew by 24 percent the last decade, net food imports by sub- over the decade, but growth may have been Saharan Africa, measured in constant prices, dampened by the rising use of domestic increased more than 60 percent, implying grains for biofuel production. a further widening of the food trade deficit faced by this region over the past Food imports by region several decades, as population growth has Food imports have been rising more rapidly outstripped growth in food production. in Asia than in any other region (Figure 27), increasing in volume terms by almost 75 percent between 2000 and 2010. Imports continued to grow through the food price crisis and also during the recession, as the region succeeded in sustaining relatively high rates of income growth. Food imports by countries in the Near East and North Africa have also grown, financed by growing oil revenues, but were considerably reduced during the recession. Imports by all other regions also grew significantly over time, with the exception of North America and Oceania, where they remained relatively stagnant. Sub-Saharan Africa’s food import volumes increased during the first half of the decade, but the higher international prices during the food price crisis and the
  • 87. W o r ld food a n d a g r icul t u r e i n r e v iew 75 FIGURE 26 Indices of food export volumes by geographic region, 2000–10 Index (2004–06 = 100) 200 Northern America Latin America and 180 the Caribbean 160 Western Europe Eastern Europe 140 Near East and North Africa 120 Sub-Saharan Africa 100 Asia Oceania and Japan 80 60 40 20 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Note: Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates. Source: FAO. FIGURE 27 Indices of food import volumes by geographic region, 2000–10 Index (2004–06 = 100) 140 Northern America 130 Latin America and the Caribbean 120 Western Europe 110 Eastern Europe Near East and 100 North Africa 90 Sub-Saharan Africa Asia 80 Oceania and Japan 70 60 50 40 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Note: Estimates are in constant US dollars (2004–2006 basis). Data for 2010 are projected; those for 2009 are provisional estimates. Source: FAO.
  • 88. 76 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 food price crisis and have shown substantial Recent trends in agricultural and highly correlated volatility since 2006 prices: a higher price plateau, (Figure 29). More recently, from June and greater price volatility through October 2010, prices of cereals, oils and sugar have increased, largely explaining International prices for agricultural the increase in the FPI over the same period. commodities The volatility of sugar prices, particularly As discussed above, price developments in since 2005, has been even more pronounced food commodity markets, especially those than that of the other commodities used to calculate the FPI (cereals, oils, dairy, contained in the FPI. Meat prices have meats and sugar), can have a critical impact fluctuated little in comparison with those of on global food security. Close monitoring of cereals, oils, dairy products and sugar. market developments is therefore crucial. Among other agricultural commodities This section reviews recent developments in that are not part of the FPI (Figure 28), international and domestic food markets, international fruit prices moved closely discusses the current situation and identifies together with those of the FPI, exhibiting major issues of concern for future food a spike during the food price crisis and a security. decline during the subsequent financial crisis. During the food price crisis of 2007–08 The price of beverage products moved less the FPI increased sharply (Figure 28). At the closely with prices of commodities contained time of writing, the most recent data shows in the FPI. Raw material prices were generally the FPI to have increased again from June not affected by the rise in other commodity through October 2010. In fact, by October prices during the food price crisis but 2010, the FPI was just 8 percent below its decreased significantly in response to the peak in June 2008. economic downturn in 2009 before moving Among the commodities included in the upwards again in response to economic FPI, prices for cereals, oils and dairy products recovery, reflecting the high income elasticity showed a sharp increase during the 2007–08 of demand for this group of commodities. FIGURE 28 FAO Food Price Index and indices of other commodities (fruits, beverages and raw materials), October 2000–October 2010 Index (2002–04 = 100) 250 FAO Food Price Index Fruits 200 Beverages Raw materials 150 100 50 0 Oct Oct Oct Oct Oct Oct Oct Oct Oct Oct Oct 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: FAO.
  • 89. W o r ld food a n d a g r icul t u r e i n r e v iew 77 FIGURE 29 Indices of prices of commodities included in the FAO Food Price Index (cereals, oils, dairy, meat and sugar), October 2000–October 2010 Index (2002–04 = 100) 400 Cereals Oils 350 Dairy 300 Sugar Meat 250 200 150 100 50 0 Oct Oct Oct Oct Oct Oct Oct Oct Oct Oct Oct 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Sources: FAO and IMF. Although prices of basic commodities have double threat to the food security of poor declined from the peak levels they attained consumers, as domestic food prices remained during the food price crisis, by the third high while income growth slowed or turned quarter of 2010 prices of all commodities in negative. the FPI remained significantly higher than In 2010, this double threat seems to those preceding the crisis. According to have diminished relative to the preceding projections in the OECD-FAO Agricultural period, particularly as many emerging and Outlook 2010–2019 (OECD-FAO, 2010), real developing countries appeared to have commodity prices over the next decade are recovered from the economic slowdown expected to be, on average, higher than earlier and more strongly than expected they were in the period 2000–10. Factors (See IMF, 2010c ). Moreover, the most recent underlying the projected higher agricultural available data on domestic prices indicate commodity prices include higher production that cereal prices in developing countries costs, increased demand by emerging and have declined significantly from their peaks developing countries and growing production in 2008, although at the time of writing the of biofuels from agricultural feedstocks. price of wheat on international markets had again risen sharply. Data on cereal wholesale Domestic food prices in developing prices in 74 developing countries collected countries by GIEWS (FAO, 2010j) show that, by early Last year’s edition of this report discussed 2010, such prices had fallen in nominal terms price transmission from international to relative to their peak values in 90 percent of domestic markets (FAO, 2009a). After the the countries. After adjusting for inflation, food price crisis, domestic commodity more than 98 percent of price quotes had prices in many countries were slow in fallen from their peaks by the start of 2010. moving downwards, despite the rapid fall Nevertheless, although domestic prices in in international prices, suggesting a slow developing countries have declined, they or low degree of transmission to domestic remain high compared with before the consumers. This phenomenon created a food price crisis. Indeed, in early 2010, more
  • 90. 78 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 than 80 percent of the inflation-adjusted increased fluctuations in agricultural and wholesale cereal price quotes remained food production. A further source of price above their average level in 2006 – the year volatility is the expanding production of prior to the food price crisis. biofuels based on agricultural feedstocks, which could tighten the link between prices Growing concerns over price of agricultural commodities, especially volatility maize, and developments and conditions The extreme variability of prices of basic in international energy markets, implying food commodities over the most recent an increased transmission of fluctuations in period has caused considerable concern. energy prices onto markets for agricultural Episodes of high prices are detrimental and food commodities. The close to food security, and the high uncertainty relationship between the production costs of associated with price volatility affects ethanol from maize and of petrol from crude producer viability and may lead to reduced oil is illustrated in Figure 31. This also implies agricultural investments. Data on price that prices for crude oil and for maize now volatility over a longer period (starting in appear to be closely related. In the light of 1957), show that high price volatility such current uncertainties surrounding future oil as that recently experienced is not far out prices and their impact both on demand for of line with past experiences (Figure 30). biofuels and on agricultural input markets Indeed, periods of high price volatility are (e.g. markets for fertilizers, mechanization, not new to agriculture, but there are fears and transportation), concerns over increased that price volatility may be increasing. agricultural price volatility from these new Increased disquiet over greater volatility sources appear to have some justification. of food prices is related to the emergence Furthermore, higher real crop prices have of new factors contributing to it. One also recently induced higher production important factor is the expected increase in some areas where yield volatility is also in severe weather events as a consequence higher, such as the grain-producing areas of climate change, which could lead to around the Black Sea. To the extent that FIGURE 30 Historic annualized volatility of international grain prices Percentage 70 Wheat Maize 60 Rice 50 40 30 20 10 0 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 Note: Some price variability can be predicted (e.g. seasonal variation, business cycles or other trending behaviour). The figure shows the coefficient of variation of prices after the predictable component has been removed from the observed values (for explanation, see OECD-FAO, 2010, p. 57, footnote 5). Values close to zero indicate low volatility, higher values denote greater volatility. Source: OECD-FAO, 2010.
  • 91. W o r ld food a n d a g r icul t u r e i n r e v iew 79 BOX 13 Implied volatility as a measure of uncertainty How organized commodity exchanges Implied volatilities for wheat, maize perceive and value uncertainty is and soybeans since 1990 are presented important for future decisions on in Figure A and movement over the production, trade and investment. period October 2007–October 2010 is Implied volatility represents the market’s presented in Figure B. Market perceptions expectation of how much the price of a of volatility as estimated by the commodity is likely to fluctuate in the implied price volatility have increased future. It is derived from the prices of systematically, with a sharp peak in 2008. derivative contracts, namely options, In the aftermath of the 2007–08 market which are priced on the basis of the turmoil, implied volatilities fell as markets market’s estimates of future prices as began to stabilize. However, around mid- well as the uncertainty surrounding these 2010 implied volatility started moving estimates. The more divergent are traders’ upwards again when doubts began to expectations about future prices, the emerge over Russia’s ability to meet higher the underlying uncertainty and grain export commitments, followed thus the implied volatility. (For a more by similar concerns over United States detailed discussion of the concept and the maize prospects and expected demand methodology, see FAO, 2010k.) outstripping soybean supply. Implied price volatility of wheat and maize A 1990–2010 Percentage 45 40 35 30 25 20 15 10 5 0 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 B October 2007–October 2010 Percentage 60 50 40 30 20 10 0 Oct Apr Oct Apr Oct Apr Oct 2007 2008 2008 2009 2009 2010 2010 Wheat Maize Soybeans Source: FAO.
  • 92. 80 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 FIGURE 31 Co-movement of energy production costs: ethanol from maize versus petrol from crude oil, October 2006–October 2010 US cents/litre 80 Petrol from crude oil 70 Ethanol from maize 60 50 40 30 20 10 0 Oct Apr Oct Apr Oct Apr Oct Apr Oct 2006 2007 2007 2008 2008 2009 2009 2010 2010 Notes and sources: FAO calculation using ethanol production, simple cost budgets and IMF commodity price statistics. The petroleum equivalent is the per-litre price of crude oil adjusted to an ethanol energy basis, plus a cost adjustment for processing to gasoline. Ethanol from maize is the cost of producing ethanol, net of by-product revenues, on a per-litre basis. Source prices are Brent Crude oil and US Gulf #2 Maize. these areas increase their export market Europe, but has continued to grow in other shares, greater supply volatility from these regions, although more slowly in Eastern regions may affect price volatility. Europe. Despite some fluctuations during A highly relevant factor in recent times the crises, food production increased over has been the uncoordinated national policy the last decade in all regions except Western responses to fluctuations in international Europe, as well as Japan and Oceania. With prices, which may exacerbate market the exception of Eastern Europe and Latin volatility. The impact of such policies was America and the Caribbean, which represent discussed in last year’s edition of this report key future food suppliers, supplies from (FAO, 2009a). A further issue is the role traditional exporters appear to be increasing of speculation in recent market volatility; more slowly than in the past. Food imports this has been surrounded by considerable decreased as a result of the price and controversy, and further research evidence financial crises in all regions except Asia and on the topic is needed. the Near East and North Africa. Commodity prices appear to be on a Summary of the current situation higher plateau and are projected to remain and future prospects for agricultural at levels above those of the pre-crisis period markets while markets have remained highly volatile. In the aftermath of the food price and Market volatility and its possible implications financial crises, global food and agricultural for food security have become increasingly commodity markets appear to be problematic for policy-makers worldwide. characterized both by higher price levels In an environment of increased uncertainty, and increased uncertainty. During the crises, policy responses to the situation will be per capita food consumption decreased a critical determinant of future market marginally in sub-Saharan Africa as well developments and their possible implications as in North America, Oceania and Western for food security.
  • 93. W o r ld food a n d a g r icul t u r e i n r e v iew 81 BOX 14 Price volatility and FAO’s Intergovernmental Groups on Grains and Rice The extraordinary joint intersessional • insufficient market transparency at all meeting of FAO’s Intergovernmental levels, including in relation to futures Group on Grains and Intergovernmental markets; Group on Rice held in Rome on • growing linkages with outside 24 September 2010 recognized that markets, in particular the impact of unexpected price hikes and volatility “financialization” on futures markets; are amongst the major threats to food • unexpected changes triggered by security. They pointed to a number of root national food-security situations; causes that need to be addressed: • panic buying and hoarding. • the lack of reliable and up-to-date information on crop supply and demand and export availability; Source: FAO, 2010l. of appropriate safety nets and social Conclusions programmes to protect the food-insecure The world food-price crisis, followed by the from the immediate impact of shocks like global financial crisis and economic recession, these, as well as the critical and urgent pushed the number of undernourished need to boost the productive capacity of people in the world to unprecedented developing countries and to enhance their levels in 2008 and 2009. Estimates indicate resilience to shocks. that the number of undernourished people The food price crisis has highlighted a series declined in 2010, as food prices fell from of concerns specific to the agriculture sector their peak levels and global economic and agricultural markets. First, the most conditions began to improve. However, levels recent projections by FAO and OECD indicate of undernourishment remain very high by that, although international prices fell fairly historical standards, and concerns both for rapidly from the peak levels attained during the world economy and for world agriculture the global food-price crisis, they remain continue to be at the top of the international higher than they were before the crisis and policy agenda. In October 2010, the IMF it appears that higher food prices are here indicated that “macroeconomic recovery is to stay. Agriculture faces higher production proceeding broadly as expected, although costs, increasing demand from rapidly growing downside risks remain elevated” (IMF, 2010b, countries in developing regions and expanding p. 1). At the same time, the sudden rise in biofuel production. As a result, prices are cereal prices from June through October projected to increase over the next decade 2010 raised fears of a new food-price crisis. and to continue to be at levels, on average, Whatever the short-term outlook for above those of the past decade. There is by the world economy, agriculture and food now a widely recognized need to significantly security, a number of lessons with long-term increase investments in agriculture in implications appear to have emerged or to order to generate environmentally have been confirmed from the developments sustainable productivity increases and of the past few years. expand production, while at the same time The experiences of the food price and enhancing the contribution of agriculture to financial crises have provided a sharp economic growth and poverty alleviation. reminder of the vulnerability of world A second source of concern is the recent food security to shocks in the global food turbulence in international agricultural system and the world economy and have markets and the risk of increased price demonstrated how rapidly an already volatility. Price volatility has always been a unacceptable level of food insecurity in the feature of agricultural markets; however, a world can deteriorate in the face of such number of trends appear to be accentuating events. This has underscored the importance this phenomenon. Climate change may
  • 94. 82 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 be leading to more frequent and extreme security and hunger-reduction efforts, there weather events and to the consequent risk is a need to address issues of governance on of shocks to agricultural markets. Expanding global agricultural markets with a view to production of biofuels based on agricultural confronting the problem of price volatility commodities will make agricultural markets and avoiding counter-productive “beggar- much more dependent on developments in thy-neighbour” policy responses. Necessary global energy markets. steps would include improved regulation A specific “human-induced” threat to of markets, greater market transparency, market stability is that of uncoordinated improved and timely statistics on food national policy responses to increasing food commodity markets, establishment of an prices. Because such measures are based appropriate level of emergency stocks and exclusively on concerns about domestic food provision of adequate and appropriate security, with little regard for their effects safety nets. The recent food and financial on trading partners, they may exacerbate crises, the uncoordinated policy responses international market volatility and and continuing fears over global food- jeopardize global food security. market turmoil have underscored the Given the importance of international urgent need for action by the international food commodity markets for global food community.
  • 97. S t a t is t ic a l a n n ex 85 Notes on the annex tables Symbols The following symbols are used in the tables: .. = data not available 0 or 0.0 = nil or negligible blank cell = not applicable (A) = FAO estimate Numbers displayed in the tables might be slightly different from the ones obtained from the original data sources because of rounding or data processing. To separate decimals from whole numbers a full point (.) is used. Technical notes Table A1: Total population, female share of population and rural share of population in 1980, 1995 and 2010 Source: FAO, 2010b. Total population The de facto population in a country, area or region as of 1 July of the year indicated. Figures are presented in the thousands. Female share of population The total number of women divided by the total population and multiplied by 100. Rural share of population The de facto population living in areas classified as rural (according to the criteria used by each country) divided by the total population and multiplied by 100. Table A2: Female share of national, rural and urban population aged 15–49, most recent and earliest observations Source: United Nations, 2008. Data presented are not directly comparable among countries because they vary in terms of year(s) of data collection. For details, refer to United Nations (2008). Rural/urban The population classified as rural or urban according to criteria used by each country.
  • 98. 86 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 Table A3: Economically active population, female share of economically active population and agricultural share of economically active women in 1980, 1995 and 2010 Source: FAO, 2010b. Economically active population The number of all employed and unemployed persons (including those seeking work for the first time). The term covers employers; self-employed workers; salaried employees; wage earners; unpaid workers assisting in a family, farm or business operation; members of producers’ cooperatives; and members of the armed forces. The economically active population is also referred to as the labour force. Female share of economically active population The share of all employed and unemployed persons who are female (including those seeking work for the first time). The term covers female employers; self-employed workers; salaried employees; wage earners; unpaid workers assisting in a family, farm or business operation; members of producers’ cooperatives; and members of the armed forces. The economically active female population is also referred to as the female labour force. Agricultural share of economically active women The share of the economically active female population who are engaged in or seeking work in agriculture, hunting, fishing or forestry. Table A4 : Economically active population, agricultural share of economically active population and female share of economically active in agriculture in 1980, 1995 and 2010 Source: FAO, 2010b. Economically active population See notes for Table A3. Agricultural share of the economically active population The share of the economically active population who are engaged in or seeking work in agriculture, hunting, fishing or forestry. Female share of economically active in agriculture The share of the economically active population in agriculture who are women. Table A5: Share of households in rural areas that are female- headed, most recent and earliest observations, and total agricultural holders and female share of agricultural holders, most recent observations Sources: Measure DHS/ICF Macro, 2010 (columns 1 and 2), and FAO, 2011 (forthcoming) (columns 3 and 4). Households Values are based on de jure members, i.e. usual residents. Agricultural holder The definition of agricultural holder varies from country to country, but widely refers to the person or group of persons who make the
  • 99. S t a t is t ic a l a n n ex 87 major decisions regarding resource use and exercise management control over the agricultural holding operation. The agricultural holder has technical and economic responsibility for the holding and may undertake all responsibilities directly, or delegate responsibilities related to the management of day-to-day work. The agricultural holder is often, but not always, the household head. Symbols used (B) Indicates that the source is FAO (2010f). (1) Data are from the Northeast Region only. (2) In Kyrgyzstan and Lebanon the landless holders are without arable land (rather than without any land). (3) In the case of Viet Nam, farm owners (rather than agricultural holders) were counted. (4) Data were collected for ever-married women aged 10-49. Women age 10–14 were removed from the data set and the weights recalculated for the 15–49 age group. (5) Data were collected for women aged 10-49 and indicators were calculated for women 15-49. (6) Data were collected for women aged 13-49 and indicators were calculated for women 15-49. (7) For Austria, Belgium, Denmark, Finland, Germany, Greece, Ireland, Luxembourg, Netherlands, Norway, Portugal and Sweden, holders include “holders without agricultural land”. Table A6: Share of adult population with chronic energy deficiency (CED – body mass index less than 18.5) by sex and share of children underweight by sex, residence and household wealth quintile, most recent observations Source: WHO, 2010. Share of women with CED The share of adult women who have a body mass index (BMI) (kg/m2) less than 18.5. Share of men with CED The share of adult men who have a body mass index (BMI) (kg/m2) less than 18.5. Share of children underweight Underweight prevalence, among children under five years of age (0–59 months unless otherwise noted) is estimated as the share of those children whose weight is below minus two standard deviations from the median weight for age of the National Center for Health Statistics (NCHS)/WHO/Centers for Disease Control and Statistics (CDC) international standard reference population. Residence Criteria used to define rural and urban are often country-specific; data in this table are based on national definitions. Household wealth quintile Household ownership of assets and access to services is measured and principle components analysis is used to calculate an index, the value of which is assigned to each member of the household. The index
  • 100. 88 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 scores for the entire population are then arranged in ascending order and the distribution is divided at the points that form the five 20 percent cohorts. Symbols used and additional notes on the data (C) Indicates no observations available for both men and women from the same year for chronic energy deficiency (CED). For share of underweight children, observations are for children aged 0–59 months unless indicated by: (1) 6–59 months, (2) 0–71 months, (3) 3–59 months (4) 6–39 months and (5) 24–59 months. The national BMI data displayed in this table are empirical and it has been verified that they apply internationally recommended BMI cut-off points. However, it should be noted the data presented are not directly comparable because they vary in terms of sampling procedures, age ranges and the year(s) of data collection. For details, refer to WHO, 2010. Country groups and aggregates The tables in this publication contain country group composites for all indicators for which aggregates can be calculated. These are generally weighted averages that are calculated for the country groupings as described below. In general, an aggregate is shown for a country grouping only when data are available for at least half the countries and represent at least two-thirds of the available population in that classification. Country and regional notes Regional and subregional groupings, as well as the designation of developing and developed regions, follow the standard country or area codes for statistical use developed by the United Nations Statistics Division. They are available at http://unstats.un.org/unsd/methods/ m49/m49regin.htm Whenever possible, data from 1992 or later are shown for the individual countries of Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. Data before 1992 are shown under the Union of Soviet Socialist Republics (“USSR” in the table listings). Separate observations are shown for Belgium and Luxembourg whenever possible. Unless otherwise noted, data for China include data for Hong Kong Special Administrative Region of China, Macao Special Administrative Region of China, and Taiwan Province of China. Data for China, mainland do not include those areas. Data are shown when possible for the individual countries formed from the former Czechoslovakia – the Czech Republic and Slovakia. Data before 1993 are shown under Czechoslovakia.
  • 101. S t a t is t ic a l a n n ex 89 Data are shown for Eritrea and Ethiopia separately, if possible; in most cases before 1992 data on Eritrea and Ethiopia are aggregated and presented as Ethiopia PDR. Data for Yemen refer to that country from 1990 onward; data for previous years refer to aggregated data of the former People’s Democratic Republic of Yemen and the former Yemen Arab Republic. Data for years prior to 1992 are provided for the former Yugoslavia (“Yugoslavia SFR” in the table listings). Observations from the years 1992 to 2006 are provided for the individual countries formed from the former Yugoslavia; these are Bosnia and Herzegovina, Croatia, the former Yugoslav Republic of Macedonia, and Slovenia, as well as Serbia and Montenegro. Observations are provided separately for Serbia and for Montenegro after the year 2006 when Serbia and Montenegro separated and became two independent states.
  • 102. 90 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A1 Total population, female share of population and rural share of population in 1980, 1995 and 2010 Population Total Female share Rural share (Thousands) (% of total) (% of total) 1980 1995 2010 1980 1995 2010 1980 1995 2010 WORLD 4 428 081 5 713 069 6 908 685 49.7 49.6 49.6 60.9 55.3 49.4 COUNTRIES IN DEVELOPING 3 299 983 4 538 389 5 671 456 49.0 49.1 49.2 70.7 62.4 54.7 REGIONS AFRICA 482 232 726 284 1 033 043 50.3 50.2 50.1 72.1 65.8 59.9 Sub-Saharan Africa 389 751 593 182 863 315 50.4 50.4 50.2 76.1 69.3 62.5 Eastern Africa 143 491 219 874 327 187 50.6 50.6 50.4 85.3 80.4 76.2 Burundi 4 130 6 167 8 519 51.9 51.3 50.9 95.7 92.8 89.0 Comoros 384 615 890 49.7 49.8 49.9 76.8 71.7 71.8 Djibouti 340 624 879 50.3 50.2 50.1 27.9 20.2 11.9 Eritrea 3 206 5 224 51.2 50.8 83.4 78.4 Ethiopia 56 983 84 976 50.3 50.2 86.1 82.4 Ethiopia PDR (A) 37 878 50.4 89.3 Kenya 16 261 27 492 40 863 50.2 50.2 50.0 84.3 81.0 77.8 Madagascar 8 604 13 121 20 146 49.7 50.0 50.2 81.5 74.2 69.8 Malawi 6 215 10 144 15 692 51.6 50.6 50.3 90.9 86.7 80.2 Mauritius 966 1 129 1 297 50.7 50.1 50.5 57.7 56.7 57.4 Mozambique 12 138 15 945 23 406 51.1 52.3 51.3 86.9 73.8 61.6 Réunion 506 664 837 51.2 51.1 51.3 46.6 13.9 6.0 Rwanda 5 197 5 440 10 277 52.0 52.1 51.5 95.3 91.7 81.2 Seychelles 66 76 85 50.0 50.0 49.4 50.0 50.0 44.7 Somalia 6 434 6 521 9 359 50.6 50.5 50.4 73.2 68.6 62.5 Uganda 12 655 20 954 33 796 50.2 50.2 49.9 92.5 88.3 86.7 United Republic of Tanzania 18 661 29 972 45 040 50.6 50.5 50.1 85.4 79.5 73.6 Zambia 5 774 9 108 13 257 50.3 50.3 50.1 60.2 62.9 64.3 Zimbabwe 7 282 11 713 12 644 50.3 50.6 51.6 77.6 68.3 61.7 Middle Africa 53 793 86 423 128 908 50.9 50.6 50.4 71.0 65.2 56.9 Angola 7 854 12 539 18 993 50.8 50.7 50.7 75.7 56.0 41.5 Cameroon 9 080 14 054 19 958 50.4 50.3 50.0 68.1 54.7 41.6 Central African Republic 2 269 3 335 4 506 50.9 50.9 50.9 66.1 62.8 61.1 Chad 4 608 7 128 11 506 50.8 50.5 50.3 81.2 78.1 72.4 Congo 1 815 2 782 3 759 50.3 50.2 50.1 52.1 43.6 37.9 Democratic Republic 27 170 44 921 67 827 51.1 50.6 50.4 71.3 71.6 64.8 of the Congo Equatorial Guinea 220 452 693 51.4 50.7 50.4 72.3 61.1 60.3 Gabon 682 1 084 1 501 50.7 50.5 50.0 45.3 24.6 14.0 Sao Tome and Principe 95 128 165 50.5 50.0 50.3 66.3 51.6 37.6 Northern Africa 112 990 163 943 212 920 49.8 49.7 49.8 59.9 53.6 48.3 Algeria 18 811 28 265 35 423 49.8 49.6 49.5 56.5 44.0 33.5
  • 103. S t a t is t ic a l a n n ex 91 TABLE A1 (cont.) Population Total Female share Rural share (Thousands) (% of total) (% of total) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Egypt 44 433 63 858 84 474 49.9 49.6 49.7 56.1 57.2 57.2 Libyan Arab Jamahiriya 3 063 4 834 6 546 46.6 47.6 48.4 29.9 24.0 22.1 Morocco 19 567 26 951 32 381 50.0 50.3 50.9 58.8 48.3 43.3 Sudan 20 509 30 841 43 192 49.9 49.7 49.6 80.0 68.7 54.8 Tunisia 6 457 8 935 10 374 49.3 49.5 49.7 49.4 38.5 32.7 Western Sahara 150 259 530 46.0 47.9 47.2 22.7 12.7 18.1 Southern Africa 32 972 47 240 57 968 50.5 50.9 50.7 55.3 48.6 41.2 Botswana 985 1 550 1 978 51.2 50.6 49.9 83.6 51.0 38.9 Lesotho 1 296 1 726 2 084 53.9 53.4 52.7 88.5 83.0 73.1 Namibia 1 013 1 620 2 212 51.2 51.1 50.7 74.9 70.2 62.0 South Africa 29 075 41 375 50 492 50.3 50.7 50.7 51.6 45.5 38.3 Swaziland 603 969 1 202 52.6 52.0 51.0 82.3 77.0 74.5   Western Africa 138 986 208 804 306 060 50.1 50.0 49.9 72.8 64.1 55.4 Benin 3 560 5 723 9 212 51.6 50.3 49.5 72.7 63.3 58.0 Burkina Faso 6 862 10 127 16 287 50.5 50.6 50.0 91.2 84.9 79.6 Cape Verde 289 398 513 54.3 52.8 52.0 76.5 51.3 38.8 Côte d’Ivoire 8 419 14 981 21 571 48.0 48.2 49.1 63.1 58.6 49.9 Gambia 616 1 085 1 751 50.6 50.5 50.4 71.6 56.1 41.9 Ghana 11 026 17 245 24 333 49.5 49.4 49.3 68.8 59.9 48.5 Guinea 4 628 7 478 10 324 49.8 49.5 49.5 76.4 70.5 64.6 Guinea-Bissau 836 1 166 1 647 50.6 50.5 50.5 82.4 70.2 70.0 Liberia 1 910 1 945 4 102 50.7 50.6 50.3 64.8 50.0 38.5 Mali 7 183 9 549 13 323 49.9 50.5 50.6 81.5 74.5 66.7 Mauritania 1 525 2 270 3 366 49.8 49.7 49.3 72.7 60.2 58.6 Niger 5 922 9 302 15 891 50.2 50.4 49.9 86.6 84.2 83.3 Nigeria 74 523 110 449 158 259 50.3 50.2 49.9 71.4 61.1 50.2 Saint Helena 5 5 4 60.0 60.0 50.0 60.0 60.0 75.0 Senegal 5 636 8 660 12 861 49.4 50.1 50.4 64.2 60.2 57.1 Sierra Leone 3 261 3 989 5 836 51.4 51.5 51.3 70.9 65.8 61.6 Togo 2 785 4 432 6 780 50.7 50.6 50.5 75.3 66.8 56.6 ASIA EXCLUDING JAPAN 2 450 128 3 322 591 4 039 744 48.6 48.7 48.7 64.9 57.4 50.7 Central Asia 53 399 61 349 50.8 50.9 57.0 57.7 Kazakhstan 15 926 15 753 51.7 52.4 44.1 41.5 Kyrgyzstan 4 592 5 550 50.8 50.6 63.7 63.4 Tajikistan 5 775 7 075 50.0 50.6 71.1 73.5 Turkmenistan 4 187 5 177 50.6 50.7 54.7 50.5 Uzbekistan 22 919 27 794 50.4 50.3 61.6 63.1
  • 104. 92 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A1 (cont.) Population Total Female share Rural share (Thousands) (% of total) (% of total) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Eastern Asia excluding 1 042 581 1 286 233 1 436 956 48.6 48.4 48.2 78.0 66.2 53.2 Japan China(A) 986 220 1 217 595 1 361 763 48.5 48.3 48.1 80.0 68.3 54.8 China, Hong Kong SAR 5 039 6 214 7 069 47.9 50.3 52.6 8.5 0.0 0.0 China, Macao SAR 252 412 548 49.2 51.7 52.4 1.6 0.0 0.0 China, mainland 963 123 1 189 612 1 330 840 49.4 49.2 48.9 81.8 69.9 56.0 Democratic People’s 17 239 21 717 23 991 51.3 50.9 50.6 43.1 40.9 36.6 Republic of Korea Mongolia 1 663 2 270 2 701 49.9 50.0 50.6 47.9 43.2 42.5 Republic of Korea 37 459 44 651 48 501 49.9 49.9 50.5 43.3 21.8 18.1 Southeastern Asia 355 774 479 834 589 616 50.2 50.2 50.2 74.5 64.7 51.8 Brunei Darussalam 193 295 407 46.6 47.5 48.4 39.9 31.5 24.3 Cambodia 6 748 11 380 15 053 53.7 51.9 51.0 91.0 85.8 77.2 Indonesia 146 582 191 501 232 517 49.9 49.9 50.1 77.9 64.4 46.3 Lao People’s Democratic 3 238 4 809 6 436 50.3 50.0 50.1 87.6 82.6 66.8 Republic Malaysia 13 763 20 594 27 914 49.7 49.2 49.2 58.0 44.3 27.8 Myanmar 33 561 43 864 50 496 50.6 50.7 51.2 76.0 73.9 66.1 Philippines 48 112 69 965 93 617 49.6 49.6 49.6 62.5 46.0 33.6 Singapore 2 415 3 480 4 837 48.9 49.7 49.8 0.0 0.0 0.0 Thailand 47 264 60 140 68 139 49.9 50.5 50.8 73.2 69.7 66.0 Timor-Leste 581 849 1 171 49.1 48.6 49.1 83.6 77.4 71.9 Viet Nam 53 317 72 957 89 029 51.5 51.3 50.6 80.8 77.8 71.2 Southern Asia 949 618 1 332 534 1 719 122 48.0 48.3 48.6 76.6 72.3 68.1 Afghanistan 13 946 18 084 29 117 48.1 48.2 48.2 84.3 80.2 75.2 Bangladesh 90 397 128 086 164 425 48.5 49.2 49.4 85.1 78.3 71.9 Bhutan 423 509 708 48.2 49.1 47.3 89.8 79.4 63.1 India 692 637 953 148 1 214 464 48.0 48.1 48.4 76.9 73.4 69.9 Iran (Islamic Republic of) 39 330 62 205 75 078 48.8 49.1 49.2 50.3 39.8 30.5 Maldives 158 248 314 47.5 48.8 49.4 77.8 74.2 59.6 Nepal 15 058 21 624 29 853 48.7 49.9 50.3 93.9 89.1 81.8 Pakistan 82 609 130 397 184 753 47.4 48.2 48.5 71.9 68.2 63.0 Sri Lanka 15 060 18 233 20 410 49.0 49.8 50.8 81.2 83.6 84.9 Western Asia 102 155 170 591 232 701 48.8 48.7 48.6 48.6 37.6 33.7 Armenia 3 223 3 090 52.6 53.4 33.7 36.3 Azerbaijan 7 784 8 934 51.1 51.1 47.8 47.8 Bahrain 347 578 807 41.8 41.7 42.6 13.8 11.6 11.4 Cyprus 611 731 880 50.1 50.1 51.3 41.4 32.0 29.8 Georgia 5 069 4 219 52.5 53.0 46.1 47.0 Iraq 14 024 20 971 31 467 49.0 49.8 49.4 34.5 31.2 33.6 Israel 3 764 5 374 7 285 50.0 50.7 50.4 11.4 9.1 8.3
  • 105. S t a t is t ic a l a n n ex 93 TABLE A1 (cont.) Population Total Female share Rural share (Thousands) (% of total) (% of total) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Jordan 2 225 4 304 6 472 48.3 47.7 48.7 40.0 21.8 21.5 Kuwait 1 375 1 725 3 051 42.7 39.9 40.6 5.2 1.9 1.6 Lebanon 2 785 3 491 4 255 50.4 50.8 51.0 26.3 15.2 12.8 Occupied Palestinian 1 476 2 617 4 409 48.4 49.3 49.1 37.5 29.6 27.9 Territory (A) Oman 1 187 2 172 2 905 47.3 41.0 43.7 52.5 28.3 28.3 Qatar 229 526 1 508 36.2 34.0 24.6 10.5 5.9 4.2 Saudi Arabia 9 604 18 255 26 246 46.0 44.2 45.3 34.1 21.3 17.9 Syrian Arab Republic 8 971 14 610 22 505 49.6 49.6 49.5 53.3 49.9 45.1 Turkey 46 161 61 206 75 705 49.5 49.6 49.8 56.2 37.9 30.4 United Arab Emirates 1 015 2 432 4 707 30.9 33.9 32.9 19.3 21.6 21.9 Yemen 8 381 15 523 24 256 50.1 49.3 49.4 83.5 76.2 68.2 LATIN AMERICA 362 654 482 265 588 647 50.1 50.4 50.6 35.1 27.0 20.7 AND THE CARIBBEAN Caribbean 29 860 36 640 42 311 50.1 50.3 50.5 48.3 41.0 33.2 Anguilla 7 10 15 42.9 50.0 53.3 0.0 0.0 0.0 Antigua and Barbuda 72 68 89 51.4 51.5 50.6 65.3 66.2 69.7 Aruba 61 80 107 50.8 51.3 52.3 49.2 51.3 53.3 Bahamas 210 281 346 50.5 50.5 51.2 27.1 19.2 15.9 Barbados 249 258 257 52.2 51.9 51.4 60.2 65.5 59.1 British Virgin Islands 11 18 23 54.5 50.0 52.2 81.8 61.1 60.9 Cayman Islands 17 33 57 52.9 51.5 50.9 0.0 0.0 0.0 Cuba 9 835 10 910 11 204 49.4 49.8 49.9 31.9 25.7 24.3 Dominica 73 69 67 50.7 50.7 50.7 37.0 30.4 25.4 Dominican Republic 5 927 8 124 10 225 49.4 49.6 49.8 48.7 42.2 29.5 Grenada 89 100 104 51.7 51.0 50.0 67.4 69.0 69.2 Guadeloupe 327 405 467 51.1 51.4 52.0 2.1 1.5 1.7 Haiti 5 691 7 861 10 188 50.8 50.6 50.6 79.5 67.4 50.4 Jamaica 2 133 2 466 2 730 50.7 50.7 51.1 53.3 49.4 46.3 Martinique 326 370 406 51.5 52.2 53.2 20.2 2.2 2.0 Montserrat 12 10 6 50.0 50.0 50.0 83.3 90.0 83.3 Netherlands Antilles 174 191 201 51.7 52.4 53.7 19.0 12.0 7.0 Puerto Rico 3 197 3 701 3 998 51.3 51.7 52.1 33.1 12.9 1.2 Saint Kitts and Nevis 43 43 52 51.2 51.2 51.9 65.1 67.4 67.3 Saint Lucia 118 147 174 50.8 51.0 51.1 73.7 70.7 71.8 Saint Vincent 100 108 109 52.0 50.0 49.5 73.0 57.4 52.3 and the Grenadines Trinidad and Tobago 1 082 1 265 1 344 50.0 50.9 51.4 89.1 90.4 86.1 Turks and Caicos Islands 8 15 33 50.0 53.3 51.5 37.5 20.0 6.1 United States Virgin Islands 98 107 109 52.0 52.3 53.2 20.4 9.3 4.6  
  • 106. 94 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A1 (cont.) Population Total Female share Rural share (Thousands) (% of total) (% of total) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Central America 91 879 124 004 153 115 50.1 50.4 50.8 39.8 32.9 28.3 Belize 144 220 313 49.3 49.5 49.5 50.7 52.7 47.3 Costa Rica 2 349 3 479 4 640 49.0 49.2 49.2 56.9 44.2 35.7 El Salvador 4 663 5 728 6 194 50.8 51.6 52.9 55.9 46.0 38.7 Guatemala 7 016 10 007 14 377 49.4 50.3 51.3 62.6 56.9 50.5 Honduras 3 634 5 588 7 616 49.8 49.9 50.0 65.1 57.7 51.2 Mexico 68 872 91 650 110 645 50.2 50.5 50.8 33.7 26.6 22.2 Nicaragua 3 250 4 659 5 822 49.9 50.2 50.5 50.1 46.5 42.7 Panama 1 951 2 673 3 508 49.2 49.5 49.6 49.6 40.0 25.2 South America 240 915 321 621 393 221 50.1 50.4 50.6 31.6 23.0 16.4 Argentina 28 154 34 772 40 666 50.6 50.9 50.9 17.1 11.3 7.6 Bolivia (Plurinational 5 356 7 484 10 031 50.7 50.3 50.1 54.6 40.6 33.5 State of) Brazil 121 618 161 692 195 423 50.1 50.5 50.8 32.6 22.2 13.5 Chile 11 181 14 410 17 135 50.7 50.6 50.5 18.8 15.6 11.0 Colombia 26 891 36 459 46 300 50.2 50.6 50.8 37.9 29.5 24.9 Ecuador 7 964 11 407 13 775 49.7 49.8 49.9 53.0 42.2 33.1 Falkland Islands (Malvinas) 2 2 3 50.0 50.0 66.7 50.0 0.0 0.0 French Guiana 68 139 231 48.5 48.2 50.2 29.4 25.2 23.8 Guyana 776 759 761 50.5 51.4 48.6 69.5 70.9 71.6 Paraguay 3 199 4 802 6 460 49.6 49.4 49.5 58.3 47.9 38.5 Peru 17 328 23 943 29 496 49.7 49.8 49.9 35.4 29.7 28.4 Suriname 366 436 524 49.5 49.3 50.0 45.1 29.8 24.4 Uruguay 2 916 3 224 3 372 51.0 51.6 51.7 14.6 9.5 7.4 Venezuela (Bolivarian 15 096 22 092 29 044 49.4 49.6 49.8 20.8 13.2 6.0 Republic of) OCEANIA EXCLUDING AUSTRALIA AND 4 969 7 249 10 022 47.5 48.7 49.2 78.2 75.9 76.8 NEW ZEALAND American Samoa 33 53 69 48.5 49.1 49.3 24.2 15.1 7.2 Cook Islands 18 19 20 50.0 47.4 50.0 44.4 42.1 25.0 Fiji 634 768 854 49.4 49.2 49.3 62.1 54.6 46.6 French Polynesia 151 216 272 47.7 48.1 48.9 42.4 46.3 48.5 Guam 107 146 180 47.7 47.9 48.9 6.5 8.2 6.7 Kiribati 55 77 100 49.1 49.4 52.0 67.3 63.6 56.0 Marshall Islands 51 63 49.0 52.4 33.3 28.6 Micronesia (Federated 107 111 48.6 48.6 74.8 77.5 States of) Nauru 7 10 10 57.1 50.0 50.0 0.0 0.0 0.0 New Caledonia 143 193 254 48.3 48.7 50.0 42.7 39.9 34.6 Niue 3 2 1 66.7 50.0 100 100 50.0 100 Northern Mariana Islands 58 88 50.0 52.3 10.3 9.1 Palau 17 21 47.1 52.4 29.4 19.0
  • 107. S t a t is t ic a l a n n ex 95 TABLE A1 (cont.) Population Total Female share Rural share (Thousands) (% of total) (% of total) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Papua New Guinea 3 199 4 709 6 888 46.8 48.7 49.2 87.0 85.9 87.5 Samoa 155 168 179 49.0 48.2 48.0 78.7 78.6 76.5 Solomon Islands 229 362 536 48.0 48.1 48.1 89.5 85.4 81.3 Tokelau 2 1 1 50.0 100 100 100 100 100 Tonga 97 97 104 49.5 49.5 49.0 78.4 77.3 75.0 Tuvalu 8 9 10 50.0 55.6 50.0 75.0 55.6 50.0 Vanuatu 117 172 246 47.0 48.8 48.8 85.5 79.7 74.4 Wallis and Futuna Islands 11 14 15 54.5 50.0 53.3 100 100 100 COUNTRIES IN DEVELOPED 1 127 965 1 174 680 1 237 229 51.7 51.5 51.4 32.1 27.8 24.9 REGIONS ASIA AND OCEANIA 134 636 147 245 152 810 50.7 50.9 51.1 37.0 32.2 29.5 Australia 14 695 18 118 21 512 50.1 50.3 50.3 14.2 13.9 10.9 Japan 116 794 125 442 126 995 50.8 51.0 51.3 40.4 35.4 33.2 New Zealand 3 147 3 685 4 303 50.3 50.6 50.6 16.6 14.7 13.2 EUROPE 739 232 727 362 732 760 52.1 51.9 51.9 33.2 29.0 27.4 Eastern Europe 369 928 309 805 291 485 52.8 52.6 53.1 39.2 31.8 31.6 Belarus 10 270 9 588 53.1 53.5 32.1 25.7 Bulgaria 8 862 8 357 7 497 50.2 51.0 51.7 37.9 32.2 28.3 Czech Republic 10 319 10 411 51.4 50.9 25.4 26.5 Czechoslovakia (A) 15 260 51.3 32.5 Hungary 10 707 10 332 9 973 51.6 52.2 52.5 35.8 34.8 31.7 Poland 35 574 38 595 38 038 51.3 51.3 51.8 41.9 38.5 38.8 Republic of Moldova 4 339 3 576 52.2 52.5 53.7 58.8 Romania 22 201 22 681 21 190 50.7 51.0 51.4 53.9 46.0 45.4 Russian Federation 148 497 140 367 53.1 53.8 26.6 27.2 Slovakia 5 352 5 412 51.3 51.5 43.4 43.2 Ukraine 51 063 45 433 53.6 53.9 33.0 31.9 USSR (A) 265 407 53.4 37.4 Yugoslav SFR (A) 11 917 51.0 54.5 Northern Europe 82 479 93 260 98 907 51.1 51.3 50.9 16.8 17.0 15.6 Denmark 5 123 5 228 5 481 50.6 50.7 50.4 16.3 15.0 12.8 Estonia 1 439 1 339 53.6 53.9 30.0 30.5 Faroe Islands 43 43 50 51.2 51.2 50.0 69.8 69.8 58.0 Finland 4 780 5 108 5 346 51.7 51.3 51.0 40.2 38.6 36.1 Iceland 228 267 329 49.6 49.8 48.6 11.8 8.2 7.6 Ireland 3 401 3 609 4 589 49.7 50.3 49.9 44.7 42.1 38.1 Latvia 2 492 2 240 53.9 53.9 31.3 31.8 Lithuania 3 630 3 255 52.9 53.2 32.7 32.8
  • 108. 96 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A1 (cont.) Population Total Female share Rural share (Thousands) (% of total) (% of total) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Norway 4 086 4 359 4 855 50.4 50.6 50.3 29.4 26.2 22.4 Sweden 8 310 8 827 9 293 50.5 50.6 50.3 16.9 16.2 15.3 United Kingdom 56 508 58 258 62 130 51.3 51.4 50.9 12.2 11.2 10.1 Southern Europe 116 325 143 699 153 780 51.2 51.2 51.0 34.8 35.3 32.5 Albania 2 671 3 134 3 169 48.4 49.6 50.7 66.2 61.1 52.0 Andorra 37 65 87 48.6 47.7 48.3 8.1 6.2 11.5 Bosnia and Herzegovina 3 332 3 760 51.5 51.9 58.9 51.4 Croatia 4 669 4 410 51.8 51.8 45.1 42.2 Gibraltar 28 29 31 46.4 48.3 48.4 0.0 0.0 0.0 Greece 9 643 10 672 11 183 50.9 50.6 50.4 42.3 40.7 38.6 Holy See 1 1 1 0.0 0.0 0.0 0.0 0.0 0.0 Italy 56 307 57 207 60 098 51.5 51.6 51.3 33.4 33.1 31.6 Malta 324 378 410 51.2 50.5 50.2 10.2 9.0 5.4 Montenegro 626 50.8 40.4 Portugal 9 766 10 038 10 732 51.9 51.8 51.6 57.2 48.9 39.3 San Marino 21 26 32 47.6 46.2 46.9 19.0 7.7 6.3 Serbia (A) 9 856 50.5 47.6 Serbia and Montenegro (A) 10 828 50.4 49.0 Slovenia 1 966 2 025 51.4 51.2 49.4 52.0 Spain 37 527 39 391 45 317 51.0 51.0 50.7 27.2 24.1 22.6 The former Yugoslav 1 963 2 043 50.0 50.1 39.7 32.1 Republic of Macedonia Western Europe 170 500 180 598 188 588 51.8 51.3 51.1 27.3 25.2 23.0 Austria 7 549 7 936 8 387 52.7 51.8 51.2 34.6 34.2 32.4 Belgium 10 698 51.0 2.6 Belgium-Luxembourg (A) 10 192 10 493 51.1 51.1 5.2 3.8 France 53 950 57 999 62 637 51.2 51.4 51.4 26.7 25.1 22.2 Germany 78 289 81 622 82 057 52.4 51.4 50.9 27.2 26.7 26.2 Liechtenstein 25 31 36 52.0 51.6 52.8 84.0 83.9 86.1 Luxembourg 492 50.4 17.7 Monaco 26 31 33 53.8 51.6 51.5 0.0 0.0 0.0 Netherlands 14 150 15 448 16 653 50.4 50.6 50.4 35.3 27.2 17.1 Switzerland 6 319 7 038 7 595 51.4 51.2 51.2 42.9 26.4 26.4 NORTHERN AMERICA 254 097 300 073 351 659 50.9 50.9 50.6 26.1 22.7 17.9 Bermuda 56 61 65 48.2 49.2 49.2 0.0 0.0 0.0 Canada 24 516 29 302 33 890 50.2 50.5 50.5 24.3 22.3 19.4 Greenland 50 56 57 48.0 48.2 49.1 24.0 19.6 15.8 Saint Pierre and Miquelon 6 6 6 50.0 50.0 50.0 16.7 16.7 16.7 United States of America 229 469 270 648 317 641 51.0 50.9 50.6 26.3 22.7 17.7
  • 109. S t a t is t ic a l a n n ex 97 TABLE A2 Female share of national, rural and urban population aged 15–49, most recent and earliest observations Most recent observation Earliest observation (1999–2008) (1960–1980) (%) (%) National Rural Urban National Rural Urban WORLD COUNTRIES IN DEVELOPING REGIONS AFRICA Sub-Saharan Africa Eastern Africa Burundi .. .. .. 50.1 50.2 46.2 Comoros .. .. .. 52.2 52.6 51.0 Djibouti .. .. .. .. .. .. Eritrea .. .. Ethiopia 50.0 49.9 50.5 Ethiopia PDR .. .. .. Kenya 50.9 54.3 38.9 51.1 53.2 37.6 Madagascar .. .. .. 51.6 51.5 51.8 Malawi 51.4 52.1 48.7 53.3 54.5 42.6 Mauritius 49.7 49.6 49.9 .. .. .. Mozambique .. .. .. .. .. .. Réunion .. .. .. .. .. .. Rwanda 52.9 55.0 44.3 52.3 53.1 40.8 Seychelles .. .. .. 51.7 50.6 54.8 Somalia 50.5 50.1 51.2 .. .. .. Uganda 52.3 52.5 51.5 50.2 51.1 42.3 United Republic of Tanzania .. .. .. 52.4 53.7 45.9 Zambia 51.7 52.4 50.5 53.1 56.8 47.9 Zimbabwe 52.3 53.2 50.9 .. .. .. Middle Africa Angola .. .. .. .. .. .. Cameroon .. .. .. 53.3 56.0 47.3 Central African Republic .. .. .. 54.5 55.2 53.1 Chad .. .. .. .. .. .. Congo .. .. .. .. .. .. Democratic Republic of the Congo .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. Gabon .. .. .. .. .. .. Sao Tome and Principe 51.4 49.5 52.8 .. .. .. Northern Africa 49.3 50.7 47.1 Algeria .. .. .. 50.7 50.8 50.5
  • 110. 98 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A2 (cont.) Most recent observation Earliest observation (1999–2008) (1960–1980) (%) (%) National Rural Urban National Rural Urban Egypt .. .. .. 50.5 51.2 49.3 Libyan Arab Jamahiriya 49.5 49.9 49.5 48.2 49.5 47.2 Morocco 51.2 51.0 51.4 51.8 52.2 51.0 Sudan .. .. .. 51.4 53.7 45.1 Tunisia .. .. .. 50.3 51.8 48.4 Western Sahara .. .. .. 42.4 45.4 38.5 Southern Africa 51.7 51.7 52.3 50.1 53.5 43.3 Botswana 52.4 50.9 53.2 52.5 52.6 47.5 Lesotho 50.8 49.2 54.9 .. .. .. Namibia 51.6 52.6 50.1 48.7 52.3 39.2 South Africa 52.0 54.0 50.7 49.0 55.6 43.2 Swaziland .. .. .. .. .. .. Western Africa Benin 54.0 55.7 51.8 57.4 59.1 55.0 Burkina Faso 54.2 55.9 49.7 52.7 53.0 48.9 Cape Verde 51.4 52.5 50.6 .. .. .. Côte d’Ivoire .. .. .. 48.7 51.7 43.4 Gambia .. .. .. .. .. .. Ghana 51.3 51.1 51.4 .. .. .. Guinea .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. Liberia .. .. .. 52.2 54.9 46.3 Mali .. .. .. .. .. .. Mauritania .. .. .. .. .. .. Niger 51.3 51.6 50.0 .. .. .. Nigeria .. .. .. 51.3 52.6 45.2 Saint Helena .. .. .. .. .. .. Senegal 53.7 54.4 53.0 52.6 53.0 51.8 Sierra Leone .. .. .. .. .. .. Togo .. .. .. .. .. .. ASIA EXCLUDING JAPAN 49.5 49.2 49.5 Central Asia 50.2 49.5 51.0 49.8 50.0 49.6 Kazakhstan 50.6 48.5 52.3 49.8 48.5 50.8 Kyrgyzstan 50.1 49.0 52.0 49.8 49.6 50.2 Tajikistan 50.1 50.3 49.5 50.0 50.7 48.8 Turkmenistan .. .. .. 49.7 50.5 48.8 Uzbekistan 50.2 50.3 50.0 49.9 50.4 49.2 Eastern Asia excluding Japan 49.3 47.8 49.9 China 48.7 48.6 48.8 .. .. ..
  • 111. S t a t is t ic a l a n n ex 99 TABLE A2 (cont.) Most recent observation Earliest observation (1999–2008) (1960–1980) (%) (%) National Rural Urban National Rural Urban China, Hong Kong SAR .. .. .. .. .. .. China, Macao SAR .. .. .. 50.7 48.4 50.8 China, mainland .. .. .. .. .. .. Democratic People’s Republic of Korea .. .. .. .. .. .. Mongolia 50.3 48.5 51.4 .. .. .. Republic of Korea 49.1 46.4 49.6 50.3 50.2 50.4 Southeastern Asia 50.2 49.7 50.7 Brunei Darussalam 49.8 47.8 50.5 47.1 50.0 43.9 Cambodia 51.1 50.9 51.9 50.5 50.7 48.5 Indonesia 50.3 50.1 50.5 52.7 52.7 53.0 Lao People’s Democratic Republic 50.4 50.6 50.0 .. .. .. Malaysia 49.2 48.6 49.5 .. .. .. Myanmar .. .. .. .. .. .. Philippines .. .. .. 51.3 50.3 53.1 Singapore .. .. .. .. .. .. Thailand 50.4 50.0 51.5 50.5 50.5 50.7 Timor-Leste .. .. .. .. .. .. Viet Nam 50.2 49.8 51.2 .. .. .. Southern Asia 49.4 49.9 47.9 48.7 49.4 44.9 Afghanistan .. .. .. 49.2 49.3 48.3 Bangladesh 50.0 51.4 46.2 48.4 49.4 39.5 Bhutan 46.1 47.2 44.2 .. .. .. India 48.2 48.7 47.0 48.4 49.5 43.9 Iran (Islamic Republic of) 49.3 49.2 49.3 48.7 49.7 47.1 Maldives 50.8 50.6 51.1 46.5 46.3 48.5 Nepal 50.9 51.6 48.2 51.5 51.8 45.6 Pakistan 49.6 50.2 48.7 47.7 48.9 40.9 Sri Lanka 50.2 50.5 48.6 48.9 49.9 45.4 Western Asia 48.9 48.5 49.1 47.2 48.5 46.0 Armenia 50.7 49.2 51.6 50.7 49.8 51.1 Azerbaijan 50.3 49.8 50.7 50.2 52.1 48.9 Bahrain .. .. .. 43.4 49.2 42.0 Cyprus 50.8 49.2 51.5 52.0 53.0 50.4 Georgia 51.7 49.7 53.5 51.5 50.4 52.4 Iraq 49.8 50.3 49.6 49.9 51.4 48.3 Israel 49.8 48.7 49.9 50.2 48.6 50.5 Jordan 48.2 48.0 48.3 48.4 49.0 47.9 Kuwait .. .. .. .. .. .. Lebanon .. .. .. 49.5 50.0 49.2 Occupied Palestinian Territory .. .. .. Oman 38.5 40.3 37.9 .. .. ..
  • 112. 100 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A2 (cont.) Most recent observation Earliest observation (1999–2008) (1960–1980) (%) (%) National Rural Urban National Rural Urban Qatar .. .. .. .. .. .. Saudi Arabia .. .. .. .. .. .. Syrian Arab Republic 50.0 50.3 49.9 49.5 50.5 47.9 Turkey 49.1 49.9 48.7 48.5 51.4 42.0 United Arab Emirates .. .. .. 22.5 26.8 21.8 Yemen .. .. .. .. .. .. LATIN AMERICA AND THE CARIBBEAN 50.7 48.3 51.8 50.9 48.6 53.3 Caribbean Anguilla .. .. .. .. .. .. Antigua and Barbuda .. .. .. 53.5 52.4 55.0 Aruba .. .. .. .. .. .. Bahamas .. .. .. .. .. .. Barbados .. .. .. .. .. .. British Virgin Islands .. .. .. .. .. .. Cayman Islands .. .. .. .. .. .. Cuba 49.3 47.7 49.8 49.2 46.7 50.7 Dominica .. .. .. .. .. .. Dominican Republic 50.4 49.5 50.8 50.7 48.3 55.5 Grenada .. .. .. .. .. .. Guadeloupe .. .. .. .. .. .. Haiti 51.2 47.7 56.6 .. .. .. Jamaica 51.3 48.9 53.3 53.4 51.9 56.2 Martinique .. .. .. .. .. .. Montserrat .. .. .. .. .. .. Netherlands Antilles .. .. .. 50.5 50.8 51.4 Puerto Rico .. .. .. 52.5 51.8 52.9 Saint Kitts and Nevis .. .. .. 55.1 54.6 56.2 Saint Lucia 50.9 51.0 50.6 .. .. .. Saint Vincent and the Grenadines .. .. .. .. .. .. Trinidad and Tobago .. .. .. .. .. .. Turks and Caicos Islands .. .. .. .. .. .. United States Virgin Islands .. .. .. 49.3 46.4 51.5 Central America 51.6 50.2 52.7 50.9 48.4 54.2 Belize 51.4 50.5 52.2 51.5 46.4 55.7 Costa Rica 51.1 50.0 51.9 50.4 47.7 53.9 El Salvador 54.1 53.2 54.6 52.1 49.9 55.3 Guatemala 52.7 51.9 53.3 49.7 48.2 52.4 Honduras 51.0 48.4 53.2 51.3 50.3 54.2 Mexico 52.2 52.3 52.2 51.2 49.5 52.7 Nicaragua 50.9 48.6 52.6 51.9 48.6 56.6 Panama 49.7 46.9 51.6 49.5 46.6 53.0
  • 113. S t a t is t ic a l a n n ex 101 TABLE A2 (cont.) Most recent observation Earliest observation (1999–2008) (1960–1980) (%) (%) National Rural Urban National Rural Urban South America 50.1 46.8 51.1 50.2 47.3 52.2 Argentina 49.9 47.0 50.2 50.3 45.4 51.2 Bolivia (Plurinational State of) 50.1 46.8 51.6 51.2 50.5 52.0 Brazil 50.8 46.8 51.6 50.9 49.0 52.9 Chile 49.8 46.2 50.3 51.6 45.3 54.1 Colombia 51.5 47.0 52.7 52.0 48.3 55.2 Ecuador 49.8 48.4 50.4 50.8 49.3 53.5 Falkland Islands (Malvinas) .. .. .. 42.1 40.1 44.2 French Guiana .. .. .. .. .. .. Guyana 50.1 49.0 52.6 50.5 49.7 54.5 Paraguay 49.4 46.1 51.7 52.1 50.7 54.3 Peru 50.7 48.0 51.4 50.5 50.9 50.0 Suriname 49.2 48.3 49.6 .. .. .. Uruguay 50.3 43.4 50.8 50.7 41.7 52.6 Venezuela (Bolivarian Republic of) 49.8 44.7 50.4 .. .. .. OCEANIA EXCLUDING AUSTRALIA AND NEW ZEALAND American Samoa .. .. .. .. .. .. Cook Islands .. .. .. .. .. .. Fiji 48.8 47.4 50.0 49.6 49.8 49.2 French Polynesia .. .. .. .. .. .. Guam .. .. .. .. .. .. Kiribati 51.0 49.9 52.3 51.6 53.2 47.2 Marshall Islands .. .. .. .. .. .. Micronesia (Federated States of) .. .. .. .. .. .. Nauru .. .. .. .. .. .. New Caledonia .. .. .. .. .. .. Niue .. .. .. .. .. .. Northern Mariana Islands 61.2 66.3 60.5 .. .. .. Palau .. .. .. .. .. .. Papua New Guinea 49.1 49.8 45.4 47.6 49.2 39.3 Samoa .. .. .. 48.6 48.4 49.6 Solomon Islands .. .. .. 48.2 50.2 29.9 Tokelau .. .. .. .. .. .. Tonga 49.5 49.3 49.9 .. .. .. Tuvalu .. .. .. .. .. .. Vanuatu .. .. .. 47.3 49.0 37.6 Wallis and Futuna Islands .. .. .. .. .. .. COUNTRIES IN DEVELOPED REGIONS 49.5 47.9 50.2 ASIA AND OCEANIA 50.1 49.3 50.2 49.8 47.9 50.1 Australia 49.8 48.9 50.0 48.7 44.8 49.5
  • 114. 102 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A2 (cont.) Most recent observation Earliest observation (1999–2008) (1960–1980) (%) (%) National Rural Urban National Rural Urban Japan 49.4 49.5 49.4 51.4 52.4 50.9 New Zealand 51.0 49.4 51.2 49.3 46.4 49.8 EUROPE 49.5 47.7 50.4 Eastern Europe 49.7 47.9 50.6 51.5 51.4 51.4 Belarus 50.2 47.0 51.1 52.6 52.9 52.2 Bulgaria 49.2 46.9 50.0 49.7 49.7 49.6 Czech Republic 48.7 47.8 49.0 Czechoslovakia .. .. .. Hungary 49.4 47.8 50.2 51.6 51.7 51.4 Poland 49.5 48.1 50.4 52.5 52.7 52.4 Republic of Moldova 50.3 48.9 52.0 51.9 51.3 52.7 Romania 49.2 46.6 51.1 50.6 51.0 49.8 Russian Federation 50.6 48.9 51.2 50.2 48.1 51.0 Slovakia 49.2 48.2 50.1 .. .. .. Ukraine 50.6 48.7 51.4 52.8 54.0 52.0 USSR .. .. .. Yugoslav SFR .. .. .. Northern Europe 49.2 47.2 50.1 49.6 46.8 51.7 Denmark .. .. .. 50.1 45.7 51.5 Estonia 50.3 48.0 51.4 50.1 47.4 51.1 Faroe Islands 46.4 45.7 47.6 46.4 44.6 50.4 Finland 49.0 47.6 49.5 50.8 47.3 53.3 Iceland 47.8 43.9 48.1 49.2 47.2 51.5 Ireland 49.8 47.9 51.0 49.8 45.8 53.9 Latvia 50.0 47.2 51.4 50.5 48.4 51.3 Lithuania 50.2 47.2 51.6 50.7 48.9 51.6 Norway 49.0 47.4 49.5 49.3 46.6 51.4 Sweden .. .. .. 49.5 45.7 50.7 United Kingdom 50.4 49.7 50.6 .. .. .. Southern Europe 49.5 47.9 50.5 Albania 50.9 50.2 51.7 .. .. .. Andorra .. .. .. .. .. .. Bosnia and Herzegovina .. .. .. .. .. .. Croatia 49.6 47.6 51.1 .. .. .. Gibraltar .. .. .. .. .. .. Greece 49.1 45.3 50.1 51.4 52.7 50.7 Holy See .. .. .. .. .. .. Italy .. .. .. .. .. .. Malta 48.9 47.4 48.9 .. .. ..
  • 115. S t a t is t ic a l a n n ex 103 TABLE A2 (cont.) Most recent observation Earliest observation (1999–2008) (1960–1980) (%) (%) National Rural Urban National Rural Urban Montenegro 49.8 47.3 51.2 .. .. .. Portugal 50.2 49.6 51.2 51.9 51.2 54.0 San Marino .. .. .. .. .. .. Serbia 49.8 47.7 51.1 Serbia and Montenegro .. .. .. Slovenia 48.4 47.9 48.8 .. .. .. Spain 49.4 48.0 50.1 51.0 49.8 52.3 The former Yugoslav Republic of Macedonia .. .. .. Western Europe Austria 49.5 48.3 50.1 50.7 49.6 51.7 Belgium 49.5 48.7 49.5 .. .. .. Belgium-Luxembourg .. .. .. .. .. .. France 50.1 48.2 50.6 49.4 47.6 50.2 Germany .. .. .. .. .. .. Liechtenstein .. .. .. .. .. .. Luxembourg .. .. .. 49.8 48.5 50.6 Monaco .. .. .. .. .. .. Netherlands 49.5 49.0 49.8 49.2 48.1 49.6 Switzerland 49.5 48.8 49.7 49.6 48.2 50.7 NORTHERN AMERICA 48.9 47.2 49.2 49.8 47.0 51.2 Bermuda .. .. .. .. .. .. Canada 50.4 49.3 50.7 49.6 46.8 50.8 Greenland 46.5 43.2 47.1 48.8 45.4 51.0 Saint Pierre and Miquelon .. .. .. .. .. .. United States of America 49.7 49.1 49.9 50.9 48.8 51.7
  • 116. 104 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A3 Economically active population, female share of economically active population and agricultural share of economically active women in 1980, 1995 and 2010 Economically active population Total Female share Agricultural share of (Thousands) (% of total) economically active women (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 WORLD 1 894 978 2 575 394 3 282 308 38.1 39.6 40.5 53.5 48.7 42.0 COUNTRIES IN DEVELOPING 1 353 280 2 000 716 2 656 880 36.4 38.3 39.2 72.1 62.8 52.7 REGIONS AFRICA 172 652 268 197 407 905 38.5 39.5 41.4 78.8 70.9 62.2 Sub-Saharan Africa 147 699 227 175 346 919 41.8 42.4 43.8 79.1 72.7 65.0 Eastern Africa 61 341 97 031 152 689 46.2 47.2 48.3 91.0 86.5 79.2 Burundi 1 977 2 978 4 260 53.2 52.3 51.4 97.8 97.6 97.3 Comoros 151 250 387 43.0 42.8 43.7 93.8 88.8 82.8 Djibouti 133 249 381 42.9 43.4 43.3 91.2 87.0 79.4 Eritrea 1 200 2 086 42.1 40.9 83.4 78.5 Ethiopia 24 306 41 929 43.6 47.9 83.3 73.5 Ethiopia PDR (A) 14 833 41.1 88.6 Kenya 6 718 12 139 18 887 45.7 46.3 46.4 88.1 82.9 73.9 Madagascar 3 880 5 966 10 060 48.6 48.3 49.1 92.7 85.8 76.4 Malawi 2 876 4 302 6 542 51.6 50.2 49.8 96.1 95.1 94.0 Mauritius 370 485 589 29.7 33.0 37.0 27.3 11.3 5.5 Mozambique 5 951 7 547 10 778 51.2 55.5 55.8 97.0 95.5 94.0 Réunion 170 270 362 35.3 43.3 46.4 8.3 0.9 0.6 Rwanda 2 328 2 327 4 722 52.6 52.7 53.1 98.0 97.3 96.1 Seychelles 28 33 40 46.4 48.5 47.5 92.3 81.3 78.9 Somalia 2 437 2 565 3 731 38.0 38.4 39.2 90.2 85.4 76.7 Uganda 5 679 9 225 14 896 47.5 47.7 47.8 90.8 86.2 77.5 United Republic of Tanzania 9 084 14 855 22 339 50.2 49.8 49.7 91.8 89.6 84.0 Zambia 1 985 3 481 5 146 36.3 42.9 43.3 84.7 79.7 68.0 Zimbabwe 2 741 4 853 5 554 46.8 46.7 44.2 84.5 78.2 68.2 Middle Africa 21 068 33 670 50 767 42.7 42.0 41.8 85.4 79.9 70.2 Angola 3 421 5 397 8 447 45.7 45.6 47.3 87.3 84.4 80.6 Cameroon 3 402 5 086 7 622 43.2 40.1 41.7 86.5 77.3 54.1 Central African Republic 1 018 1 476 2 030 46.6 45.8 44.9 90.3 83.9 70.3 Chad 1 547 2 790 4 623 25.9 45.8 49.0 95.3 88.3 76.2 Congo 700 1 099 1 524 40.3 42.1 40.6 80.5 63.3 44.4 Democratic Republic of 10 558 17 137 25 488 43.8 40.5 38.5 83.7 79.1 72.6 the Congo Equatorial Guinea 87 174 268 33.3 32.8 32.5 93.1 89.5 87.4 Gabon 305 472 708 44.9 44.1 43.9 73.7 50.0 26.7 Sao Tome and Principe 30 39 57 33.3 33.3 40.4 80.0 84.6 69.6
  • 117. S t a t is t ic a l a n n ex 105 TABLE A3 (cont.) Economically active population Total Female share Agricultural share of (Thousands) (% of total) economically active women (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Northern Africa 31 554 50 078 74 694 20.4 23.9 28.3 78.2 58.5 42.8 Algeria 4 555 9 018 14 950 21.4 25.6 34.0 69.3 51.0 32.9 Egypt 11 780 18 531 27 492 16.9 22.1 25.7 82.7 55.3 39.3 Libyan Arab Jamahiriya 838 1 517 2 425 13.4 18.3 24.5 62.5 20.9 8.6 Morocco 5 848 9 015 11 963 21.3 24.2 24.8 72.3 59.7 49.1 Sudan 6 601 9 056 13 708 26.5 26.7 31.3 88.4 80.3 65.1 Tunisia 1 865 2 829 3 886 19.0 23.4 27.4 52.7 37.3 24.6 Western Sahara 67 112 270 31.3 33.9 38.5 76.2 57.9 42.3 Southern Africa 10 753 16 325 21 371 41.2 43.5 45.9 23.2 14.4 9.8 Botswana 332 506 741 38.3 42.9 43.6 74.8 54.8 55.1 Lesotho 538 720 895 50.7 51.5 52.3 64.1 57.1 50.6 Namibia 309 507 769 47.2 45.4 46.8 63.7 47.8 31.9 South Africa 9 350 14 220 18 481 40.3 42.9 45.5 15.8 8.1 4.2 Swaziland 224 372 485 48.7 49.5 49.7 63.3 47.8 31.5 Western Africa 47 936 71 093 108 384 38.0 37.7 39.6 70.3 60.2 50.7 Benin 1 168 2 240 3 778 33.6 40.2 40.8 68.7 59.9 43.0 Burkina Faso 2 989 4 421 7 425 46.4 47.6 47.1 92.8 93.4 93.3 Cape Verde 90 131 195 40.0 38.2 42.6 38.9 28.0 16.9 Côte d’Ivoire 3 096 5 407 8 106 30.4 29.2 30.5 75.0 65.9 45.0 Gambia 273 483 806 46.2 45.5 46.8 92.9 90.5 86.5 Ghana 4 473 7 247 11 116 49.5 49.2 49.0 56.8 53.4 49.3 Guinea 2 210 3 535 4 968 47.5 46.9 47.1 96.4 90.3 84.3 Guinea-Bissau 331 451 613 39.3 40.1 38.2 97.7 96.1 94.4 Liberia 711 719 1 509 40.4 39.8 40.3 88.9 80.4 68.6 Mali 1 963 2 508 3 517 35.0 34.6 38.4 92.3 86.2 73.6 Mauritania 603 913 1 441 42.6 42.5 43.2 79.4 62.4 62.6 Niger 1 965 3 045 5 228 33.7 32.3 31.3 97.6 97.4 97.0 Nigeria 23 353 33 165 49 144 34.4 33.6 36.9 57.4 39.4 26.8 Saint Helena 2 2 2 50.0 50.0 50.0 100.0 0.0 0.0 Senegal 2 382 3 591 5 626 40.1 40.7 43.2 89.9 84.0 77.2 Sierra Leone 1 265 1 546 2 197 52.6 50.4 51.1 82.0 78.8 72.6 Togo 1 062 1 689 2 713 39.8 38.3 38.1 66.9 62.9 57.8 ASIA EXCLUDING JAPAN 1 052 771 1 533 185 1 964 239 36.7 38.5 38.4 76.0 67.5 57.6 Central Asia 21 059 29 095 46.7 47.0 25.0 17.8 Kazakhstan 7 773 8 427 47.6 49.8 12.6 6.8 Kyrgyzstan 1 885 2 547 45.5 42.6 23.9 14.6 Tajikistan 1 678 2 896 46.7 46.8 41.8 31.1 Turkmenistan 1 635 2 437 46.4 47.1 39.3 33.4
  • 118. 106 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A3 (cont.) Economically active population Total Female share Agricultural share of (Thousands) (% of total) economically active women (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Uzbekistan 8 088 12 788 46.2 46.2 31.2 20.2 Eastern Asia excluding 526 764 737 152 855 786 43.0 45.0 45.5 77.1 71.1 61.8 Japan China (A) 504 496 704 769 817 033 43.2 45.2 45.6 78.2 73.1 64.0 China, Hong Kong SAR 2 415 3 086 3 759 33.8 39.0 47.4 1.2 0.5 0.1 China, Macao SAR China, mainland Democratic People’s 7 103 10 400 12 979 39.7 41.1 44.8 52.0 37.0 23.9 Republic of Korea Mongolia 574 862 1 204 46.5 46.3 50.2 36.0 26.6 17.1 Republic of Korea 14 591 21 121 24 570 37.0 39.6 41.2 46.9 14.9 5.5 Southeastern Asia 147 907 221 405 299 123 41.2 41.9 41.6 64.2 57.1 47.8 Brunei Darussalam 71 131 195 23.9 35.9 43.6 5.9 0.0 0.0 Cambodia 3 209 4 930 8 029 54.0 51.6 48.3 80.0 76.4 69.8 Indonesia 55 181 84 276 115 905 34.9 37.8 36.9 55.8 53.4 44.2 Lao People’s Democratic 1 463 2 172 3 281 49.8 50.0 50.3 82.3 80.2 77.8 Republic Malaysia 4 984 8 167 12 445 34.5 33.9 35.8 49.3 19.3 7.5 Myanmar 15 972 22 769 29 464 44.9 45.2 46.3 80.3 75.8 70.0 Philippines 17 861 28 019 39 967 38.4 37.1 38.8 37.0 28.1 20.9 Singapore 1 117 1 740 2 637 34.6 38.7 42.1 1.3 0.1 0.0 Thailand 23 709 33 490 39 198 46.9 45.5 46.5 74.2 60.8 47.1 Timor-Leste 242 332 461 39.7 38.0 40.6 94.8 92.1 88.2 Viet Nam 24 098 35 379 47 541 49.3 49.8 48.5 75.3 71.0 64.0 Southern Asia 348 669 496 504 699 660 26.6 28.3 29.6 81.5 70.5 60.4 Afghanistan 4 548 5 620 9 384 24.1 22.4 23.4 86.0 83.9 82.0 Bangladesh 38 345 56 409 78 232 37.7 38.2 40.3 80.9 69.9 57.4 Bhutan 146 150 326 25.3 18.7 33.1 97.3 96.4 97.2 India 259 177 364 665 491 326 26.8 28.2 28.6 82.6 71.5 61.8 Iran (Islamic Republic of) 11 064 18 288 30 746 19.7 24.9 30.2 50.0 40.1 33.3 Maldives 46 70 150 21.7 27.1 42.0 40.0 21.1 14.3 Nepal 5 837 8 061 12 936 33.7 40.2 45.7 98.0 98.0 97.8 Pakistan 23 563 35 980 67 292 8.1 12.2 20.3 87.7 68.7 56.9 Sri Lanka 5 943 7 261 9 268 31.3 33.0 38.2 58.0 48.6 41.6 Western Asia 29 431 57 065 80 575 21.3 26.1 25.7 72.2 50.2 35.8 Armenia 1 375 1 575 48.4 50.2 8.0 3.0 Azerbaijan 3 229 4 633 47.3 47.9 33.1 25.6 Bahrain 136 263 384 11.0 18.3 21.6 0.0 0.0 0.0 Cyprus 282 343 446 31.9 38.5 45.7 36.7 11.4 4.9 Georgia 2 508 2 278 47.1 46.7 20.5 11.7 Iraq 3 097 5 018 7 918 12.8 14.2 17.5 62.0 32.0 15.7
  • 119. S t a t is t ic a l a n n ex 107 TABLE A3 (cont.) Economically active population Total Female share Agricultural share of (Thousands) (% of total) economically active women (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Israel 1 271 2 039 2 935 36.2 43.6 47.0 3.7 1.7 0.8 Jordan 444 1 160 1 882 11.9 14.1 17.6 58.5 35.6 22.4 Kuwait 457 823 1 541 14.2 21.5 24.7 0.0 0.0 0.0 Lebanon 857 1 190 1 563 19.8 23.7 26.0 20.0 7.1 2.2 Occupied Palestinian 465 866 1 508 26.0 26.3 26.0 57.9 36.0 22.2 Territory (A) Oman 341 778 1 123 17.3 12.5 20.4 25.4 17.5 10.5 Qatar 106 284 976 9.4 13.0 11.0 0.0 0.0 0.0 Saudi Arabia 2 415 5 752 9 570 9.9 11.2 16.0 25.1 7.6 1.8 Syrian Arab Republic 2 020 4 240 7 365 13.6 22.0 21.7 78.2 65.8 56.0 Turkey 15 299 22 518 25 942 25.8 28.1 25.5 87.9 79.1 66.3 United Arab Emirates 548 1 309 2 914 5.1 11.8 15.3 0.0 0.0 0.0 Yemen 1 693 3 370 6 022 20.3 19.8 25.1 98.3 83.2 61.9 LATIN AMERICA AND 125 954 196 316 280 321 30.4 35.6 41.8 20.6 11.2 7.4 THE CARIBBEAN Caribbean 10 733 14 496 18 380 35.6 35.3 40.8 24.5 15.5 12.2 Anguilla 2 4 7 50.0 25.0 42.9 0.0 0.0 0.0 Antigua and Barbuda 26 27 38 34.6 37.0 42.1 22.2 10.0 12.5 Aruba 22 32 46 36.4 34.4 43.5 25.0 18.2 10.0 Bahamas 88 140 186 43.2 45.0 48.4 2.6 1.6 0.0 Barbados 111 144 154 44.1 47.9 48.1 8.2 4.3 2.7 British Virgin Islands 4 7 10 25.0 42.9 40.0 0.0 0.0 25.0 Cayman Islands 6 13 25 33.3 38.5 40.0 50.0 20.0 10.0 Cuba 3 495 4 853 5 239 31.0 35.4 39.7 10.4 7.4 5.0 Dominica 26 27 29 38.5 37.0 41.4 20.0 20.0 8.3 Dominican Republic 1 834 2 925 4 491 27.5 27.1 44.8 11.1 8.8 7.3 Grenada 32 40 45 37.5 35.0 40.0 25.0 14.3 11.1 Guadeloupe 126 184 213 44.4 47.3 50.7 10.7 2.3 0.0 Haiti 2 344 2 692 3 940 44.7 33.2 33.1 61.0 53.9 44.0 Jamaica 951 1 177 1 218 46.6 47.2 44.4 18.1 13.5 10.9 Martinique 127 170 185 45.7 49.4 51.9 6.9 3.6 1.0 Montserrat 4 4 3 50.0 25.0 33.3 0.0 0.0 0.0 Netherlands Antilles 69 82 98 37.7 45.1 49.0 0.0 0.0 0.0 Puerto Rico 909 1 278 1 512 29.6 37.9 43.1 0.4 0.4 0.2 Saint Kitts and Nevis 15 17 23 40.0 35.3 39.1 16.7 16.7 11.1 Saint Lucia 39 61 84 30.8 41.0 41.7 25.0 16.0 11.4 Saint Vincent and 32 43 54 31.3 34.9 40.7 20.0 13.3 13.6 the Grenadines Trinidad and Tobago 428 519 716 35.5 38.9 44.4 8.6 4.5 2.5 Turks and Caicos Islands 3 6 14 33.3 33.3 42.9 0.0 0.0 16.7 United States Virgin Islands 40 51 50 50.0 49.0 52.0 25.0 16.0 11.5
  • 120. 108 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A3 (cont.) Economically active population Total Female share Agricultural share of (Thousands) (% of total) economically active women (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Central America 29 939 46 462 64 495 30.8 31.7 36.5 18.3 9.9 6.1 Belize 39 75 131 17.9 29.3 36.6 14.3 4.5 2.1 Costa Rica 849 1 411 2 109 27.7 31.4 35.2 4.7 6.1 5.5 El Salvador 1 592 2 201 2 587 33.9 36.3 41.1 8.5 6.5 5.3 Guatemala 2 313 2 941 5 367 25.6 23.9 38.3 16.9 14.2 10.0 Honduras 1 144 1 999 2 782 26.7 32.3 31.5 40.3 22.2 15.8 Mexico 22 318 35 202 47 529 31.3 32.2 36.6 19.2 9.6 5.5 Nicaragua 1 016 1 531 2 395 33.2 28.9 32.2 15.7 7.0 3.5 Panama 668 1 102 1 595 31.1 32.9 37.7 4.8 2.8 1.5 South America 85 282 135 358 197 446 29.6 37.0 43.6 20.8 11.1 7.3 Argentina 10 231 14 320 19 094 28.6 36.7 41.8 3.1 2.6 1.9 Bolivia (Plurinational 1 908 2 837 4 849 32.8 42.0 45.5 53.3 43.3 37.8 State of) Brazil 44 710 70 889 101 026 29.4 36.9 44.2 26.3 11.2 6.1 Chile 3 756 5 632 7 302 29.0 31.9 37.1 6.4 5.7 5.1 Colombia 8 764 15 077 23 927 33.0 39.9 46.6 23.0 11.5 7.8 Ecuador 2 543 4 260 6 320 24.9 33.6 40.8 21.8 14.7 11.2 Falkland Islands (Malvinas) 1 1 2 0.0 0.0 50.0 French Guiana 29 56 91 37.9 39.3 46.2 18.2 13.6 7.1 Guyana 252 301 347 25.0 35.5 35.4 11.1 6.5 3.3 Paraguay 1 267 2 045 3 358 38.4 39.6 45.9 8.6 6.6 4.2 Peru 5 597 9 948 15 497 29.6 40.1 44.5 25.1 20.9 17.0 Suriname 106 142 195 32.1 33.1 36.9 20.6 14.9 11.1 Uruguay 1 242 1 511 1 654 37.8 41.4 44.4 3.8 3.8 3.5 Venezuela (Bolivarian 4 876 8 339 13 784 25.4 31.1 39.9 1.9 1.5 0.8 Republic of) OCEANIA EXCLUDING AUSTRALIA AND 1 903 3 018 4 415 39.3 44.1 45.8 80.5 73.3 67.0 NEW ZEALAND American Samoa 11 20 28 27.3 35.0 39.3 66.7 42.9 27.3 Cook Islands 6 7 8 33.3 42.9 37.5 50.0 33.3 33.3 Fiji 208 291 348 21.2 31.6 32.8 27.3 26.1 23.7 French Polynesia 56 89 122 33.9 38.2 39.3 47.4 35.3 25.0 Guam 43 67 88 37.2 37.3 40.9 25.0 20.0 13.9 Kiribati 22 35 48 36.4 40.0 43.8 25.0 21.4 14.3 Marshall Islands 23 31 39.1 45.2 22.2 14.3 Micronesia (Federated 49 54 36.7 40.7 22.2 13.6 States of) Nauru 3 5 5 33.3 40.0 40.0 0.0 0.0 0.0 New Caledonia 49 81 108 36.7 37.0 38.0 55.6 43.3 31.7 Niue 1 1 1 0.0 0.0 0.0 Northern Mariana Islands 26 43 38.5 44.2 20.0 15.8 Palau 8 10 37.5 40.0 33.3 25.0
  • 121. S t a t is t ic a l a n n ex 109 TABLE A3 (cont.) Economically active population Total Female share Agricultural share of (Thousands) (% of total) economically active women (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Papua New Guinea 1 278 1 987 3 054 43.3 48.0 49.0 91.5 86.9 79.0 Samoa 54 61 65 33.3 32.8 33.8 50.0 35.0 27.3 Solomon Islands 85 144 222 40.0 40.3 38.7 85.3 84.5 80.2 Tokelau 1 1 0 0.0 0.0 Tonga 25 33 41 20.0 36.4 43.9 60.0 33.3 27.8 Tuvalu 3 4 4 33.3 25.0 50.0 0.0 0.0 0.0 Vanuatu 54 81 129 44.4 46.9 46.5 54.2 42.1 30.0 Wallis and Futuna Islands 4 5 6 25.0 40.0 33.3 100.0 50.0 50.0 COUNTRIES IN DEVELOPED 541 644 574 678 625 428 42.3 44.3 46.0 13.4 6.2 3.0 REGIONS ASIA AND OCEANIA 64 518 77 780 77 707 38.4 40.8 42.7 12.4 5.7 2.5 Australia 6 750 9 068 11 315 36.7 42.7 45.7 3.9 3.8 3.8 Japan 56 431 66 883 64 067 38.7 40.5 42.1 13.5 6.0 2.1 New Zealand 1 337 1 829 2 325 34.0 44.0 46.4 7.0 6.8 5.9 EUROPE 351 529 341 936 363 492 43.4 44.6 46.6 17.5 8.6 4.1           Eastern Europe 189 751 149 744 147 999 48.7 47.5 48.6 22.6 11.7 5.5 Belarus 5 016 4 880   48.4 49.1   9.6 3.4 Bulgaria 4 718 3 709 3 334 47.9 47.9 46.8 21.9 8.7 2.4 Czech Republic 5 160 5 242   44.3 44.5   7.0 3.2 Czechoslovakia (A) 8 116   45.8   11.8   Hungary 5 058 4 188 4 318 43.4 43.4 45.6 15.2 8.2 3.7 Poland 17 568 17 438 17 275 45.5 45.5 45.7 31.9 23.3 13.5 Republic of Moldova 1 962 1 343   48.7 52.6   21.0 8.5 Romania 10 508 12 122 9 307 46.8 46.3 45.7 45.3 21.3 8.7 Russian Federation 72 466 76 217   47.8 49.8   7.8 4.0 Slovakia 2 481 2 757   44.7 44.9   7.4 3.4 Ukraine 25 202 23 326   50.0 49.7   12.6 5.7 USSR (A) 137 459   49.7   20.3   Yugoslav SFR (A) 6 324   45.8   32.2             Northern Europe 40 445 46 413 51 420 40.6 45.0 46.6 2.7 2.4 1.4 Denmark 2 666 2 822 2 914 44.9 45.3 47.2 2.8 2.4 1.3 Estonia 713 688   48.2 50.7   9.0 4.6 Faroe Islands 22 22 26 40.9 40.9 46.2 0.0 0.0 0.0 Finland 2 468 2 490 2 724 46.2 47.5 48.3 10.3 5.1 2.7 Iceland 121 153 195 44.6 47.1 46.2 3.7 4.2 2.2 Ireland 1 246 1 466 2 328 27.8 37.7 43.6 6.1 2.5 1.1 Latvia 1 207 1 219   48.1 48.5   9.8 4.7 Lithuania 1 790 1 544   47.7 49.8   9.8 3.6
  • 122. 110 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A3 (cont.) Economically active population Total Female share Agricultural share of (Thousands) (% of total) economically active women (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Norway 2 006 2 234 2 616 41.4 45.8 47.7 6.0 3.6 2.8 Sweden 4 437 4 555 5 029 45.1 47.4 47.6 3.7 2.4 1.7 United Kingdom 27 479 28 961 32 137 39.4 44.3 46.1 1.4 1.0 0.8           Southern Europe 46 186 61 050 71 677 32.8 39.0 43.0 21.8 12.8 6.5 Albania 1 296 1 308 1 450 43.1 40.8 42.8 62.4 55.8 42.3 Andorra 16 28 41 31.3 35.7 41.5 20.0 10.0 5.9 Bosnia and Herzegovina 1 636 1 876   46.1 46.6   10.6 3.0 Croatia 2 104 1 938   43.4 45.1   10.3 2.9 Gibraltar 12 12 15 33.3 33.3 40.0 25.0 25.0 0.0 Greece 3 881 4 537 5 218 33.8 36.7 41.2 42.3 24.9 15.3 Holy See 0 0 0         Italy 22 134 23 058 25 775 33.7 36.8 42.1 14.5 7.2 3.5 Malta 120 140 172 23.3 26.4 34.3 3.6 0.0 0.0 Montenegro 305   44.9   10.9 Portugal 4 467 4 880 5 696 39.6 44.6 46.9 33.6 18.7 12.3 San Marino 9 11 15 33.3 36.4 40.0 33.3 0.0 0.0 Serbia (A) 4 806   44.7   10.9 Serbia and Montenegro (A) 4 893     45.0     25.4   Slovenia 949 1 025   46.0 46.1   3.7 0.6 Spain 14 251 16 688 22 439 28.3 37.7 42.8 18.2 8.2 3.9 The former Yugoslav 806 906   37.2 39.4   16.7 6.2 Republic of Macedonia           Western Europe 75 147 84 729 92 396 38.2 43.1 46.1 7.3 3.3 1.5 Austria 3 244 3 845 4 295 38.4 43.0 46.1 12.2 7.0 3.3 Belgium 4 713   45.4   0.9 Belgium-Luxembourg (A) 4 040 4 337   35.8 41.1   2.1 1.5   France 24 001 25 382 28 232 40.0 44.9 46.9 7.4 3.4 1.4 Germany 35 415 39 754 41 914 38.4 42.5 45.6 8.1 3.0 1.3 Liechtenstein 11 15 18 36.4 40.0 44.4 0.0 0.0 0.0 Luxembourg 228   44.7   1.0 Monaco 11 14 16 36.4 42.9 43.8 0.0 0.0 0.0 Netherlands 5 388 7 454 8 713 31.2 41.3 45.9 3.0 2.9 2.0 Switzerland 3 037 3 928 4 267 36.5 43.3 46.6 4.4 3.9 3.0           NORTHERN AMERICA 125 597 154 962 184 229 41.2 45.4 46.2 2.1 1.3 1.0 Bermuda 28 32 34 39.3 43.8 44.1 0.0 0.0 0.0 Canada 12 102 15 023 19 320 39.7 45.0 47.5 6.1 2.3 1.9 Greenland 25 29 30 40.0 44.8 46.7 0.0 0.0 0.0 Saint Pierre and Miquelon 3 3 3 33.3 33.3 33.3 0.0 0.0 0.0 United States of America 113 439 139 875 164 842 41.4 45.4 46.0 1.6 1.2 0.9
  • 123. S t a t is t ic a l a n n ex 111 TABLE A4 Economically active population, agricultural share of economically active population and female share of economically active in agriculture in 1980, 1995 and 2010 Economically active population Total Agricultural share Female share of economically (Thousands) (% of total) active in agriculture (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 WORLD 1 894 978 2 575 394 3 282 308 50.4 46.1 39.9 40.4 41.9 42.7 COUNTRIES IN DEVELOPING 1 353 280 2 000 716 2 656 880 65.3 57.2 48.2 40.1 42.1 42.9 REGIONS AFRICA 172 652 268 197 407 905 68.4 60.3 53.1 44.3 46.4 48.5 Sub-Saharan Africa 147 699 227 175 346 919 71.9 65.4 58.4 46.0 47.1 48.7 Eastern Africa 61 341 97 031 152 689 84.7 80.6 74.5 49.6 50.6 51.3 Burundi 1 977 2 978 4 260 93.2 91.4 89.2 55.9 55.9 56.0 Comoros 151 250 387 80.8 75.6 69.5 50.0 50.3 52.0 Djibouti 133 249 381 84.2 79.9 74.0 46.4 47.2 46.5 Eritrea 1 200 2 086 78.7 73.7 44.6 43.6 Ethiopia 24 306 41 929 84.4 77.3 43.0 45.5 Ethiopia PDR (A) 14 833 88.9 41.0 Kenya 6 718 12 139 18 887 82.2 77.6 70.6 49.0 49.5 48.6 Madagascar 3 880 5 966 10 060 82.3 76.9 70.1 54.7 53.9 53.5 Malawi 2 876 4 302 6 542 87.4 85.1 79.1 56.7 56.1 59.2 Mauritius 370 485 589 27.3 14.0 8.1 29.7 26.5 25.0 Mozambique 5 951 7 547 10 778 84.8 83.6 80.5 58.6 63.4 65.2 Réunion 170 270 362 28.2 4.8 1.4 10.4 7.7 20.0 Rwanda 2 328 2 327 4 722 93.1 91.5 89.4 55.3 56.1 57.0 Seychelles 28 33 40 85.7 81.8 72.5 50.0 48.1 51.7 Somalia 2 437 2 565 3 731 77.2 72.3 65.6 44.4 45.3 45.9 Uganda 5 679 9 225 14 896 87.1 82.4 74.8 49.5 49.9 49.5 United Republic of Tanzania 9 084 14 855 22 339 85.8 82.6 75.9 53.7 54.1 55.0 Zambia 1 985 3 481 5 146 74.7 71.8 63.3 41.2 47.6 46.5 Zimbabwe 2 741 4 853 5 554 73.0 66.0 56.5 54.3 55.3 53.3 Middle Africa 21 068 33 670 50 767 73.9 67.0 57.7 49.4 50.1 50.8 Angola 3 421 5 397 8 447 76.1 73.0 69.3 52.4 52.6 55.0 Cameroon 3 402 5 086 7 622 74.5 65.3 47.7 50.1 47.4 47.3 Central African Republic 1 018 1 476 2 030 84.5 76.6 63.3 49.8 50.2 49.9 Chad 1 547 2 790 4 623 85.6 79.7 65.7 28.9 50.8 56.9 Congo 700 1 099 1 524 57.3 44.4 32.0 56.6 60.0 56.5 Democratic Republic of 10 558 17 137 25 488 71.5 64.8 57.3 51.3 49.5 48.8 the Congo Equatorial Guinea 87 174 268 77.0 71.8 64.9 40.3 40.8 43.7 Gabon 305 472 708 65.6 44.5 25.7 50.5 49.5 45.6 Sao Tome and Principe 30 39 57 70.0 64.1 56.1 38.1 44.0 50.0
  • 124. 112 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A4 (cont.) Economically active population Total Agricultural share Female share of economically (Thousands) (% of total) active in agriculture (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Northern Africa 31 554 50 078 74 694 53.1 37.8 28.3 30.1 37.0 42.8 Algeria 4 555 9 018 14 950 35.9 25.9 21.2 41.5 50.4 52.7 Egypt 11 780 18 531 27 492 53.8 35.0 25.1 25.9 34.9 40.3 Libyan Arab Jamahiriya 838 1 517 2 425 22.4 7.6 3.0 37.2 50.0 69.9 Morocco 5 848 9 015 11 963 53.0 37.1 25.5 29.0 38.9 47.7 Sudan 6 601 9 056 13 708 72.1 65.1 51.5 32.5 32.9 39.5 Tunisia 1 865 2 829 3 886 37.0 25.4 20.5 27.1 34.4 32.8 Western Sahara 67 112 270 56.7 41.1 30.4 42.1 47.8 53.7 Southern Africa 10 753 16 325 21 371 21.8 15.3 10.6 43.8 40.9 42.5 Botswana 332 506 741 61.4 44.9 42.2 46.6 52.4 56.9 Lesotho 538 720 895 45.2 43.2 39.3 72.0 68.2 67.3 Namibia 309 507 769 57.3 45.4 33.6 52.5 47.8 44.6 South Africa 9 350 14 220 18 481 17.2 11.1 6.5 37.1 31.1 29.6 Swaziland 224 372 485 52.7 39.0 28.9 58.5 60.7 54.3 Western Africa 47 936 71 093 108 384 65.7 55.6 46.4 40.7 40.9 43.3 Benin 1 168 2 240 3 778 67.0 58.7 44.3 34.5 41.1 39.6 Burkina Faso 2 989 4 421 7 425 92.2 92.3 92.1 46.7 48.1 47.7 Cape Verde 90 131 195 36.7 26.7 16.9 42.4 40.0 42.4 Côte d’Ivoire 3 096 5 407 8 106 64.6 54.1 37.9 35.3 35.6 36.2 Gambia 273 483 806 84.6 80.5 75.9 50.6 51.2 53.3 Ghana 4 473 7 247 11 116 61.6 58.2 54.5 45.6 45.1 44.3 Guinea 2 210 3 535 4 968 90.9 85.6 79.8 50.4 49.5 49.7 Guinea-Bissau 331 451 613 87.3 84.0 79.3 43.9 45.9 45.5 Liberia 711 719 1 509 76.8 70.1 62.1 46.7 45.6 44.5 Mali 1 963 2 508 3 517 88.3 83.0 74.9 36.6 35.9 37.7 Mauritania 603 913 1 441 71.1 53.9 50.2 47.6 49.2 53.9 Niger 1 965 3 045 5 228 90.2 87.2 82.9 36.5 36.1 36.6 Nigeria 23 353 33 165 49 144 53.9 38.0 24.9 36.6 34.8 39.7 Saint Helena 2 2 2 50.0 50.0 50.0 100.0 0.0 0.0 Senegal 2 382 3 591 5 626 80.4 75.0 70.2 44.9 45.5 47.4 Sierra Leone 1 265 1 546 2 197 73.0 67.9 60.1 59.0 58.5 61.7 Togo 1 062 1 689 2 713 68.7 62.7 53.4 38.8 38.4 41.3 ASIA EXCLUDING JAPAN 1 052 771 1 533 185 1 964 239 68.6 61.1 52.0 40.7 42.5 42.6 Central Asia 21 059 29 095 27.6 20.5 42.4 41.0 Kazakhstan 7 773 8 427 19.7 13.8 30.4 24.4 Kyrgyzstan 1 885 2 547 28.9 20.8 37.7 29.8 Tajikistan 1 678 2 896 37.4 27.4 52.2 53.0 Turkmenistan 1 635 2 437 35.4 29.7 51.6 53.0 Uzbekistan 8 088 12 788 31.2 21.4 46.2 43.5  
  • 125. S t a t is t ic a l a n n ex 113 TABLE A4 (cont.) Economically active population Total Agricultural share Female share of economically (Thousands) (% of total) active in agriculture (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Eastern Asia excluding 526 764 737 152 855 786 72.4 67.2 58.6 45.8 47.6 47.9 Japan China (A) 504 496 704 769 817 033 73.9 69.4 60.8 45.8 47.7 47.9 China, Hong Kong SAR 2 415 3 086 3 759 1.3 0.6 0.2 31.3 31.6 25.0 China, Macao SAR .. .. .. .. .. .. .. .. .. China, mainland .. .. .. .. .. .. .. .. .. Democratic People’s 7 103 10 400 12 979 44.2 33.8 23.3 46.7 45.0 46.0 Republic of Korea Mongolia 574 862 1 204 39.7 28.0 17.9 42.1 44.0 47.9 Republic of Korea 14 591 21 121 24 570 36.9 13.5 5.2 47.1 43.8 43.8 Southeastern Asia 147 907 221 405 299 123 63.2 56.0 46.8 41.9 42.7 42.5 Brunei Darussalam 71 131 195 5.6 1.5 0.5 25.0 0.0 0.0 Cambodia 3 209 4 930 8 029 75.5 71.9 65.9 57.3 54.9 51.2 Indonesia 55 181 84 276 115 905 57.8 51.7 41.4 33.7 39.0 39.3 Lao People’s Democratic 1 463 2 172 3 281 79.8 77.5 74.9 51.3 51.8 52.3 Republic Malaysia 4 984 8 167 12 445 40.9 22.8 12.7 41.7 28.6 21.0 Myanmar 15 972 22 769 29 464 75.9 71.9 67.1 47.5 47.6 48.3 Philippines 17 861 28 019 39 967 51.5 42.6 33.7 27.6 24.5 24.0 Singapore 1 117 1 740 2 637 1.5 0.2 0.1 29.4 25.0 0.0 Thailand 23 709 33 490 39 198 70.9 60.3 48.5 49.1 45.9 45.0 Timor-Leste 242 332 461 83.9 81.9 79.6 44.8 42.6 45.0 Viet Nam 24 098 35 379 47 541 73.2 69.4 63.2 50.7 51.0 49.1 Southern Asia 348 669 496 504 699 660 67.2 59.3 51.1 32.3 33.6 34.9 Afghanistan 4 548 5 620 9 384 70.4 65.8 59.7 29.4 28.5 32.1 Bangladesh 38 345 56 409 78 232 71.9 59.9 45.4 42.4 44.5 51.0 Bhutan 146 150 326 93.8 92.7 92.9 26.3 19.4 34.7 India 259 177 364 665 491 326 68.2 61.4 54.4 32.4 32.8 32.4 Iran (Islamic Republic of) 11 064 18 288 30 746 39.0 29.4 21.6 25.2 33.9 46.4 Maldives 46 70 150 52.2 28.6 14.7 16.7 20.0 40.9 Nepal 5 837 8 061 12 936 93.4 93.4 92.9 35.4 42.2 48.1 Pakistan 23 563 35 980 67 292 58.5 45.7 39.0 12.2 18.4 29.6 Sri Lanka 5 943 7 261 9 268 52.2 47.0 42.5 34.8 34.2 37.4 Western Asia 29 431 57 065 80 575 44.0 30.4 19.2 35.0 43.0 47.9 Armenia 1 375 1 575 14.9 9.4 25.9 16.2 Azerbaijan 3 229 4 633 29.0 22.8 53.8 53.9 Bahrain 136 263 384 3.7 1.5 0.5 0.0 0.0 0.0 Cyprus 282 343 446 25.5 10.8 5.4 45.8 40.5 41.7 Georgia 2 508 2 278 22.8 15.1 42.3 36.2 Iraq 3 097 5 018 7 918 26.6 11.9 5.5 29.7 38.2 50.3 Israel 1 271 2 039 2 935 6.1 3.2 1.7 22.1 22.7 21.6
  • 126. 114 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A4 (cont.) Economically active population Total Agricultural share Female share of economically (Thousands) (% of total) active in agriculture (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Jordan 444 1 160 1 882 16.7 11.3 6.3 41.9 44.3 62.2 Kuwait 457 823 1 541 2.0 1.2 1.0 0.0 0.0 0.0 Lebanon 857 1 190 1 563 14.0 5.1 1.8 28.3 32.8 32.1 Occupied Palestinian 465 866 1 508 23.2 14.8 8.0 64.8 64.1 72.5 Territory (A) Oman 341 778 1 123 47.2 40.6 28.5 9.3 5.4 7.5 Qatar 106 284 976 2.8 1.8 0.7 0.0 0.0 0.0 Saudi Arabia 2 415 5 752 9 570 43.0 14.1 5.1 5.8 6.0 5.7 Syrian Arab Republic 2 020 4 240 7 365 33.6 28.5 20.0 31.7 50.7 60.7 Turkey 15 299 22 518 25 942 56.2 46.2 32.3 40.4 48.2 52.3 United Arab Emirates 548 1 309 2 914 4.6 6.3 3.1 0.0 0.0 0.0 Yemen 1 693 3 370 6 022 67.9 52.4 38.8 29.3 31.4 40.1 LATIN AMERICA AND 125 954 196 316 280 321 33.6 22.0 14.8 18.6 18.1 20.9 THE CARIBBEAN Caribbean 10 733 14 496 18 380 33.6 25.3 20.4 26.0 21.6 24.5 Anguilla 2 4 7 50.0 25.0 14.3 0.0 0.0 0.0 Antigua and Barbuda 26 27 38 34.6 25.9 21.1 22.2 14.3 25.0 Aruba 22 32 46 31.8 25.0 19.6 28.6 25.0 22.2 Bahamas 88 140 186 5.7 4.3 2.7 20.0 16.7 0.0 Barbados 111 144 154 9.9 5.6 2.6 36.4 37.5 50.0 British Virgin Islands 4 7 10 25.0 28.6 20.0 0.0 0.0 50.0 Cayman Islands 6 13 25 33.3 23.1 20.0 50.0 33.3 20.0 Cuba 3 495 4 853 5 239 23.7 16.4 11.1 13.5 16.1 17.9 Dominica 26 27 29 34.6 25.9 20.7 22.2 28.6 16.7 Dominican Republic 1 834 2 925 4 491 31.7 20.8 10.5 9.6 11.5 31.2 Grenada 32 40 45 34.4 25.0 20.0 27.3 20.0 22.2 Guadeloupe 126 184 213 18.3 4.3 1.4 26.1 25.0 0.0 Haiti 2 344 2 692 3 940 70.9 67.1 58.8 38.4 26.7 24.8 Jamaica 951 1 177 1 218 31.1 22.5 17.5 27.0 28.3 27.7 Martinique 127 170 185 12.6 5.3 2.2 25.0 33.3 25.0 Montserrat 4 4 3 25.0 25.0 33.3 0.0 0.0 0.0 Netherlands Antilles 69 82 98 0.0 0.0 0.0 .. .. .. Puerto Rico 909 1 278 1 512 5.9 3.1 1.1 1.9 5.1 5.9 Saint Kitts and Nevis 15 17 23 33.3 23.5 21.7 20.0 25.0 20.0 Saint Lucia 39 61 84 33.3 24.6 20.2 23.1 26.7 23.5 Saint Vincent and 32 43 54 34.4 25.6 20.4 18.2 18.2 27.3 the Grenadines Trinidad and Tobago 428 519 716 10.7 9.6 6.6 28.3 18.0 17.0 Turks and Caicos Islands 3 6 14 33.3 33.3 21.4 0.0 0.0 33.3 United States Virgin Islands 40 51 50 32.5 23.5 18.0 38.5 33.3 33.3
  • 127. S t a t is t ic a l a n n ex 115 TABLE A4 (cont.) Economically active population Total Agricultural share Female share of economically (Thousands) (% of total) active in agriculture (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Central America 29 939 46 462 64 495 37.5 26.8 18.6 15.0 11.7 11.9 Belize 39 75 131 41.0 29.3 23.7 6.3 4.5 3.2 Costa Rica 849 1 411 2 109 32.4 22.5 15.2 4.0 8.5 12.8 El Salvador 1 592 2 201 2 587 39.8 31.6 22.7 7.3 7.5 9.6 Guatemala 2 313 2 941 5 367 52.3 50.4 38.4 8.3 6.8 10.0 Honduras 1 144 1 999 2 782 56.8 35.9 24.0 18.9 19.9 20.7 Mexico 22 318 35 202 47 529 35.3 24.4 16.2 17.0 12.7 12.3 Nicaragua 1 016 1 531 2 395 37.7 25.4 14.7 13.8 8.0 7.6 Panama 668 1 102 1 595 28.6 23.4 15.5 5.2 3.9 3.6 South America 85 282 135 358 197 446 32.3 20.0 13.0 19.1 20.5 24.6 Argentina 10 231 14 320 19 094 12.8 10.2 7.4 6.9 9.3 10.7 Bolivia (Plurinational State of) 1 908 2 837 4 849 52.8 45.3 41.1 33.0 40.1 41.8 Brazil 44 710 70 889 101 026 36.5 19.5 11.0 21.2 21.2 24.5 Chile 3 756 5 632 7 302 20.4 17.2 13.2 9.2 10.6 14.2 Colombia 8 764 15 077 23 927 38.9 22.9 14.8 19.5 19.9 24.8 Ecuador 2 543 4 260 6 320 38.7 28.0 18.5 14.0 17.6 24.8 Falkland Islands (Malvinas) 1 1 2 0.0 0.0 0.0 French Guiana 29 56 91 31.0 19.6 13.2 22.2 27.3 25.0 Guyana 252 301 347 26.6 19.3 14.7 10.4 12.1 7.8 Paraguay 1 267 2 045 3 358 39.0 32.1 24.8 8.5 8.1 7.7 Peru 5 597 9 948 15 497 39.1 31.0 24.2 19.0 27.0 31.3 Suriname 106 142 195 23.6 19.7 16.9 28.0 25.0 24.2 Uruguay 1 242 1 511 1 654 15.4 13.3 11.2 9.4 11.9 14.0 Venezuela (Bolivarian 4 876 8 339 13 784 14.8 10.1 5.3 3.3 4.6 6.4 Republic of) OCEANIA EXCLUDING AUSTRALIA AND 1 903 3 018 4 415 72.1 65.8 59.0 43.8 49.1 52.0 NEW ZEALAND American Samoa 11 20 28 45.5 40.0 28.6 40.0 37.5 37.5 Cook Islands 6 7 8 50.0 42.9 25.0 33.3 33.3 50.0 Fiji 208 291 348 46.2 41.2 35.9 12.5 20.0 21.6 French Polynesia 56 89 122 48.2 38.2 27.0 33.3 35.3 36.4 Guam 43 67 88 37.2 29.9 22.7 25.0 25.0 25.0 Kiribati 22 35 48 36.4 28.6 22.9 25.0 30.0 27.3 Marshall Islands 23 31 30.4 22.6 28.6 28.6 Micronesia (Federated 49 54 28.6 22.2 28.6 25.0 States of) Nauru 3 5 5 33.3 20.0 20.0 0.0 0.0 0.0 New Caledonia 49 81 108 49.0 39.5 30.6 41.7 40.6 39.4 Niue 1 1 1 100.0 0.0 0.0 0.0 Northern Mariana Islands 26 43 30.8 23.3 25.0 30.0 Palau 8 10 25.0 20.0 50.0 50.0
  • 128. 116 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A4 (cont.) Economically active population Total Agricultural share Female share of economically (Thousands) (% of total) active in agriculture (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Papua New Guinea 1 278 1 987 3 054 82.7 77.9 69.4 47.9 53.5 55.8 Samoa 54 61 65 48.1 39.3 27.7 34.6 29.2 33.3 Solomon Islands 85 144 222 77.6 73.6 67.6 43.9 46.2 46.0 Tokelau 1 1 0 0.0 0.0 Tonga 25 33 41 48.0 39.4 26.8 25.0 30.8 45.5 Tuvalu 3 4 4 33.3 25.0 25.0 0.0 0.0 0.0 Vanuatu 54 81 129 50.0 40.7 30.2 48.1 48.5 46.2 Wallis and Futuna Islands 4 5 6 50.0 40.0 33.3 50.0 50.0 50.0 COUNTRIES IN DEVELOPED 541 644 574 678 625 428 13.1 7.5 4.2 43.4 36.9 32.7 REGIONS ASIA AND OCEANIA 64 518 77 780 77 707 10.5 5.5 2.6 45.4 42.7 40.8 Australia 6 750 9 068 11 315 6.5 5.0 3.9 22.1 32.8 44.9 Japan 56 431 66 883 64 067 11.0 5.4 2.2 47.6 44.5 40.3 New Zealand 1 337 1 829 2 325 11.2 9.6 7.9 21.3 31.3 34.8 EUROPE 351 529 341 936 363 492 16.9 10.2 5.9 44.9 37.5 32.4 Eastern Europe 189 751 149 744 147 999 23.0 15.1 9.4 47.8 36.9 28.5 Belarus 5 016 4 880 16.2 8.9 28.8 18.7 Bulgaria 4 718 3 709 3 334 20.3 9.8 3.7 51.9 42.7 30.6 Czech Republic 5 160 5 242 9.7 6.2 32.1 23.1 Czechoslovakia (A) 8 116 13.3 40.7 Hungary 5 058 4 188 4 318 18.4 12.8 7.4 35.9 27.7 22.7 Poland 17 568 17 438 17 275 29.8 24.5 17.0 48.7 43.4 36.2 Republic of Moldova 1 962 1 343 27.5 14.9 37.2 30.0 Romania 10 508 12 122 9 307 35.0 19.2 9.2 60.6 51.4 43.2 Russian Federation 72 466 76 217 12.1 8.0 31.1 24.7 Slovakia 2 481 2 757 10.6 7.1 31.2 21.5 Ukraine 25 202 23 326 16.9 10.3 37.4 27.4 USSR (A) 137 459 21.8 46.2 Yugoslav SFR (A) 6 324 27.5 53.5 Northern Europe 40 445 46 413 51 420 4.6 4.0 2.5 23.7 26.3 25.4 Denmark 2 666 2 822 2 914 6.9 4.6 2.5 18.5 23.7 24.3 Estonia 713 688 12.9 8.9 33.7 26.2 Faroe Islands 22 22 26 4.5 4.5 3.8 0.0 0.0 0.0 Finland 2 468 2 490 2 724 12.1 6.8 3.6 39.3 35.3 36.1 Iceland 121 153 195 9.9 9.2 6.2 16.7 21.4 16.7 Ireland 1 246 1 466 2 328 18.6 11.5 6.6 9.1 8.3 7.2 Latvia 1 207 1 219 13.8 9.2 34.1 25.0 Lithuania 1 790 1 544 15.1 8.0 31.0 22.6
  • 129. S t a t is t ic a l a n n ex 117 TABLE A4 (cont.) Economically active population Total Agricultural share Female share of economically (Thousands) (% of total) active in agriculture (%) 1980 1995 2010 1980 1995 2010 1980 1995 2010 Norway 2 006 2 234 2 616 8.2 5.3 3.4 30.3 31.1 39.8 Sweden 4 437 4 555 5 029 6.1 3.7 2.3 27.3 30.0 36.0 United Kingdom 27 479 28 961 32 137 2.6 2.0 1.5 20.6 21.7 24.9 Southern Europe 46 186 61 050 71 677 18.6 11.8 6.2 38.5 42.4 45.0 Albania 1 296 1 308 1 450 57.6 51.5 41.8 46.6 44.3 43.2 Andorra 16 28 41 18.8 10.7 4.9 33.3 33.3 50.0 Bosnia and Herzegovina 1 636 1 876 8.1 2.3 60.6 59.1 Croatia 2 104 1 938 11.7 4.4 38.1 29.4 Gibraltar 12 12 15 16.7 8.3 6.7 50.0 100.0 0.0 Greece 3 881 4 537 5 218 32.1 19.7 12.0 44.6 46.5 52.6 Holy See - - - Italy 22 134 23 058 25 775 12.6 6.8 3.3 38.5 38.9 45.2 Malta 120 140 172 8.3 2.1 1.2 10.0 0.0 0.0 Montenegro 305 12.8 38.5 Portugal 4 467 4 880 5 696 26.1 15.2 9.1 50.9 54.9 63.7 San Marino 9 11 15 22.2 9.1 6.7 50.0 0.0 0.0 Serbia (A) 4 806 12.8 38.1 Serbia and Montenegro (A) 4 893 24.5 46.5 Slovenia 949 1 025 3.4 0.7 50.0 42.9 Spain 14 251 16 688 22 439 18.4 9.3 4.4 28.0 33.2 37.7 The former Yugoslav 806 906 16.7 7.5 37.0 32.4 Republic of Macedonia Western Europe 75 147 84 729 92 396 7.1 3.7 1.9 38.9 38.0 36.8 Austria 3 244 3 845 4 295 9.8 6.3 3.4 47.6 47.5 45.8 Belgium 4 713 1.3 32.2 Belgium-Luxembourg (A) 4 040 4 337 3.0 2.2 24.6 28.1 France 24 001 25 382 28 232 8.3 4.3 2.0 35.7 35.6 33.6 Germany 35 415 39 754 41 914 6.9 3.2 1.6 44.9 40.9 36.8 Liechtenstein 11 15 18 9.1 6.7 0.0 0.0 0.0 Luxembourg 228 1.3 33.3 Monaco 11 14 16 9.1 7.1 0.0 0.0 0.0 Netherlands 5 388 7 454 8 713 5.6 3.9 2.5 16.7 30.9 36.4 Switzerland 3 037 3 928 4 267 6.2 4.8 3.2 26.1 35.8 43.4 NORTHERN AMERICA 125 597 154 962 184 229 3.8 2.5 1.6 22.5 24.4 28.9 Bermuda 28 32 34 3.6 3.1 2.9 0.0 0.0 0.0 Canada 12 102 15 023 19 320 6.7 2.8 1.7 36.2 37.1 52.6 Greenland 25 29 30 4.0 3.4 0.0 0.0 0.0 .. Saint Pierre and Miquelon 3 3 3 0.0 0.0 0.0 .. .. .. United States of America 113 439 139 875 164 842 3.5 2.4 1.6 19.7 22.8 25.9
  • 130. 118 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A5 Share of households in rural areas that are female-headed, most recent and earliest observations, and total agricultural holders and female share of agricultural holders, most recent observations Share of rural households Agricultural holders that are female headed (%) (Thousands) (% of total) Most recent Earliest Total Female share observation observation WORLD COUNTRIES IN DEVELOPING REGIONS AFRICA 25.5 Sub-Saharan Africa 26.2 Eastern Africa 29.9 Burundi .. .. .. .. Comoros 31.9 .. 52 464 32.6 Djibouti .. .. .. .. Eritrea 43.2 25.9 .. .. Ethiopia 20.1 21.3 11 507 442 18.7 Ethiopia PDR .. .. .. .. Kenya 33.8 35.3 .. .. Madagascar 20.6 20.8 2 428 492 15.3 Malawi 26.3 26.1 1 561 416 32.1 Mauritius .. .. .. .. Mozambique 26.3 28.2 3 064 195 23.1 Réunion .. .. .. .. Rwanda 34.0 20.8 .. .. Seychelles .. .. .. .. Somalia .. .. .. .. Uganda 29.3 23.8 1 704 721 16.3 United Republic of Tanzania (B) 25.0 17.2 4 901 837 19.7 Zambia 25.4 18.7 1 305 783 19.2 Zimbabwe 42.6 39.4 .. .. Middle Africa 21.6 Angola 21.8 .. .. .. Cameroon 22.9 16.8 .. .. Central African Republic 18.8 .. .. .. Chad 19.1 21.5 .. .. Congo 23.4 .. .. .. Democratic Republic of the Congo 20.0 .. 4 479 600 8.9 Equatorial Guinea .. .. .. .. Gabon 25.4 .. .. .. Sao Tome and Principe .. .. .. ..
  • 131. S t a t is t ic a l a n n ex 119 TABLE A5 (cont.) Share of rural households Agricultural holders that are female headed (%) (Thousands) (% of total) Most recent Earliest Total Female share observation observation Northern Africa Algeria .. .. 1 023 799 4.1 Egypt 12.0 10.9 4 537 319 5.2 Libyan Arab Jamahiriya .. .. .. .. Morocco 12.0 13.3 1 492 844 4.4 Sudan .. .. .. .. Tunisia .. .. .. .. Western Sahara .. .. .. .. Southern Africa 46.5 Botswana .. .. 51 264 33.9 Lesotho 36.3 .. 337 795 30.8 Namibia 47.4 30.6 .. .. South Africa 50.0 .. .. .. Swaziland 52.1 .. .. .. Western Africa 19.2 14.6 Benin 21.1 14.2 .. .. Burkina Faso 7.5 5.0 886 638 8.4 Cape Verde .. .. 44 450 50.5 Côte d’Ivoire 13.3 13.2 1 117 667 10.1 Gambia .. .. 69 140 8.3 Ghana 30.8 34.6 .. .. Guinea 15.8 10.8 840 454 5.7 Guinea-Bissau .. .. .. .. Liberia 26.6 28.8 .. .. Mali 11.5 7.0 805 194 3.1 Mauritania 31.7 .. .. .. Niger 18.8 8.5 .. .. Nigeria 18.6 12.9 .. .. Saint Helena .. .. .. .. Senegal 10.7 10.5 437 036 9.1 Sierra Leone 20.7 .. .. .. Togo 22.1 .. .. .. ASIA EXCLUDING JAPAN Central Asia 17.6 Kazakhstan 22.0 23.4 .. .. Kyrgyzstan (2) 18.0 .. 246 901 12.3 Tajikistan .. .. .. ..
  • 132. 120 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A5 (cont.) Share of rural households Agricultural holders that are female headed (%) (Thousands) (% of total) Most recent Earliest Total Female share observation observation Turkmenistan 18.6 .. .. .. Uzbekistan 11.6 .. .. .. Eastern Asia excluding Japan .. .. .. .. China .. .. .. .. China, Hong Kong SAR .. .. .. .. China, Macao SAR .. .. .. .. China, mainland .. .. .. .. Democratic People’s Republic of Korea .. .. .. .. Mongolia .. .. .. .. Republic of Korea .. .. .. .. Southeastern Asia 35 581 830 13.3 Brunei Darussalam .. .. .. .. Cambodia 23.0 25.0 .. .. Indonesia (B) 12.3 12.8 20 331 746 8.8 Lao People’s Democratic Republic .. .. 667 900 9.1 Malaysia (B) .. .. 500 307 13.1 Myanmar .. .. 3 464 769 15.0 Philippines 14.4 12.1 4 768 317 10.8 Singapore .. .. .. .. Thailand .. .. 5 787 774 27.4 Timor-Leste .. .. .. .. Viet Nam (3) (B) 22.4 20.7 61 017 8.8   Southern Asia Afghanistan .. .. .. .. Bangladesh (4)(5) 13.2 8.7 .. .. Bhutan .. .. .. .. India (6) 14.9 9.1 119 621 000 10.9 Iran (Islamic Republic of) .. .. .. .. Maldives .. .. .. .. Nepal 24.0 12.4 3 364 139 8.1 Pakistan 11.0 6.8 .. .. Sri Lanka .. .. .. ..   Western Asia Armenia 33.1 25.1 .. .. Azerbaijan 24.4 .. .. .. Bahrain .. .. .. .. Cyprus .. .. 44 752 25.5 Georgia .. .. 728 950 29.1
  • 133. S t a t is t ic a l a n n ex 121 TABLE A5 (cont.) Share of rural households Agricultural holders that are female headed (%) (Thousands) (% of total) Most recent Earliest Total Female share observation observation Iraq .. .. .. .. Israel .. .. .. .. Jordan 10.9 9.0 91 585 3.0 Kuwait .. .. .. .. Lebanon (2) .. .. 194 264 7.1 Occupied Palestinian Territory .. .. .. .. Oman .. .. .. .. Qatar .. .. .. .. Saudi Arabia .. .. 242 267 0.8 Syrian Arab Republic .. .. .. .. Turkey 9.1 8.6 .. .. United Arab Emirates .. .. .. .. Yemen 9.5 12.8 .. .. LATIN AMERICA AND THE CARIBBEAN Caribbean Anguilla .. .. .. .. Antigua and Barbuda .. .. .. .. Aruba .. .. .. .. Bahamas .. .. .. .. Barbados .. .. .. .. British Virgin Islands .. .. .. .. Cayman Islands .. .. .. .. Cuba .. .. .. .. Dominica .. .. .. .. Dominican Republic (B) 29.7 18.0 243 104 10.2 Grenada .. .. .. .. Guadeloupe .. .. .. .. Haiti 38.6 32.9 .. .. Jamaica (B) .. .. 182 169 19.3 Martinique .. .. .. .. Montserrat .. .. .. .. Netherlands Antilles .. .. .. .. Puerto Rico .. .. 17 659 8.8 Saint Kitts & Nevis .. .. 3 046 27.9 Saint Lucia .. .. .. .. Saint Vincent and the Grenadines .. .. .. .. Trinidad & Tobago .. .. 19 051 14.7 Turks and Caicos Islands .. .. .. .. United States Virgin Islands .. .. .. ..
  • 134. 122 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A5 (cont.) Share of rural households Agricultural holders that are female headed (%) (Thousands) (% of total) Most recent Earliest Total Female share observation observation Central America Belize (B) .. .. 9 697 8.1 Costa Rica .. .. .. .. El Salvador .. .. .. .. Guatemala 16.1 18.0 819 162 7.8 Honduras 20.2 .. .. .. Mexico .. .. .. .. Nicaragua 19.3 20.0 196 909 18.1 Panama (B) .. .. 232 464 29.3 South America Argentina (B) .. .. 202 423 18.2 Bolivia (Plurinational State of) 17.1 17.3 .. .. Brazil (1) 13.7 16.8 .. .. Chile (B) .. .. 268 787 29.9 Colombia 21.7 16.7 .. .. Ecuador .. .. 842 882 25.4 Falkland Islands (Malvinas) .. .. .. .. French Guiana .. .. .. .. Guyana .. .. .. .. Paraguay 13.4 .. .. .. Peru (B) 16.3 13.3 1 750 640 20.4 Suriname .. .. .. .. Uruguay (B) .. .. 49 302 18.1 Venezuela (Bolivarian Republic of) .. .. .. ..   OCEANIA EXCLUDING AUSTRALIA AND NEW ZEALAND American Samoa .. .. 7 094 20.6 Cook Islands .. .. .. .. Fiji .. .. .. .. French Polynesia .. .. .. .. Guam .. .. .. .. Kiribati .. .. .. .. Marshall Islands .. .. .. .. Micronesia (Federated States of) .. .. .. .. Nauru .. .. .. .. New Caledonia .. .. .. .. Niue .. .. .. .. Northern Mariana Islands .. .. 214 9.3 Palau .. .. .. .. Papua New Guinea .. .. .. .. Samoa .. .. 14 778 1.7
  • 135. S t a t is t ic a l a n n ex 123 TABLE A5 (cont.) Share of rural households Agricultural holders that are female headed (%) (Thousands) (% of total) Most recent Earliest Total Female share observation observation Solomon Islands .. .. .. .. Tokelau .. .. .. .. Tonga .. .. .. .. Tuvalu .. .. .. .. Vanuatu .. .. .. .. Wallis and Futuna Islands .. .. .. ..   COUNTRIES IN DEVELOPED REGIONS   ASIA AND OCEANIA Australia .. .. .. .. Japan .. .. .. .. New Zealand .. .. .. .. EUROPE Eastern Europe Belarus .. .. .. .. Bulgaria .. .. .. .. Czech Republic .. .. .. .. Czechoslovakia .. .. .. .. Hungary .. .. 958 534 23.9 Poland .. .. .. .. Republic of Moldova 30.8 .. .. .. Romania .. .. .. .. Russian Federation .. .. .. .. Slovakia .. .. .. .. Ukraine 47.9 .. .. .. USSR .. .. .. .. Yugoslav SFR .. .. .. .. Northern Europe 703 649 12.0 Denmark (7) .. .. 57 310 8.7 Estonia .. .. .. .. Faroe Islands .. .. .. .. Finland (7) .. .. 75 740 10.8 Iceland (7) .. .. .. .. Ireland (7) .. .. 141 340 10.7 Latvia .. .. .. .. Lithuania .. .. .. .. Norway (7) .. .. 69 959 12.9 Sweden (7) .. .. 75 910 10.0 United Kingdom (B) .. .. 283 390 18.8
  • 136. 124 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A5 (cont.) Share of rural households Agricultural holders that are female headed (%) (Thousands) (% of total) Most recent Earliest Total Female share observation observation Southern Europe Albania .. .. .. .. Andorra .. .. .. .. Bosnia and Herzegovina .. .. .. .. Croatia .. .. .. .. Gibraltar .. .. .. .. Greece (7) .. .. 816 530 25.1 Holy See .. .. .. .. Italy (B) .. .. 1 663 510 32.2 Malta .. .. .. .. Montenegro .. .. .. .. Portugal (7) .. .. 409 308 23.2 San Marino .. .. .. .. Serbia .. .. 778 891 18.1 Serbia and Montenegro .. .. .. .. Slovenia .. .. .. .. Spain (B) .. .. 988 060 28.8 The former Yugoslav Republic of Macedonia .. .. .. .. Western Europe 1 219 730 17.3 Austria (7) .. .. 194 910 29.5 Belgium (7) .. .. 59 280 15.0 Belgium-Luxembourg .. .. .. .. France (B) .. .. 427 630 23.1 Germany (7) .. .. 440 060 8.8 Liechtenstein .. .. .. .. Luxembourg (7) .. .. 2 750 19.6 Monaco .. .. .. .. Netherlands (7) .. .. 95 100 7.8 Switzerland .. .. .. .. NORTHERN AMERICA Bermuda .. .. .. .. Canada .. .. .. .. Greenland .. .. .. .. Saint Pierre and Miquelon .. .. .. .. United States of America .. .. .. ..
  • 137. S t a t is t ic a l a n n ex 125 Table A6 Share of adult population with chronic energy deficiency (CED – body mass index less than 18.5) by sex and share of children underweight by sex, residence and household wealth quintile, most recent observations Share of adult Share of children population with CED underweight (% of total) (% of total) By sex By residence By household wealth quintile Women Men Male Female Urban Rural Poorest Richest WORLD COUNTRIES IN DEVELOPING REGIONS 18.0 17.3 14.0 19.6 AFRICA 12.5 20.6 19.2 14.5 20.8 27.8 13.5 Sub-Saharan Africa 13.0 23.1 21.6 16.8 24.0 28.8 15.3 Eastern Africa 14.5 27.6 25.3 19.3 27.3 32.3 15.5 Burundi .. .. .. .. 22.0 41.0 .. .. Comoros 10.3 .. 28.0 21.0 .. .. .. .. Djibouti (1) .. .. 34.0 33.0 30.0 42.0 .. .. Eritrea 37.3 .. 41.0 39.0 29.0 45.0 49.0 20.0 Ethiopia (C) 26.5 36.7 39.0 38.0 23.0 40.0 43.0 29.0 Ethiopia PDR .. .. .. .. .. .. .. .. Kenya (1) 12.3 .. 23.0 19.0 23.0 13.0 .. .. Madagascar 19.2 .. 41.0 38.0 35.0 41.0 46.0 29.0 Malawi 9.2 .. 20.0 19.0 16.0 20.0 23.0 14.0 Mauritius .. .. .. .. .. .. .. .. Mozambique 8.6 .. 20.0 15.0 13.0 19.0 23.0 7.0 Réunion .. .. .. .. .. .. .. .. Rwanda 9.8 .. 23.0 22.0 16.0 24.0 31.0 10.0 Seychelles .. .. .. .. .. .. .. .. Somalia .. .. 37.0 34.0 23.0 43.0 48.0 16.0 Uganda 12.1 .. 21.0 20.0 14.0 21.0 25.0 11.0 United Republic of Tanzania 10.4 .. 22.0 22.0 17.0 23.0 25.0 12.0 Zambia 9.6 .. 21.0 18.0 17.0 20.0 21.0 14.0 Zimbabwe (C) 9.2 15.5 17.0 16.0 11.0 18.0 21.0 9.0 Middle Africa 13.4 23.3 21.2 18.2 25.4 29.8 14.5 Angola .. .. 32.0 29.0 30.0 32.0 .. .. Cameroon 6.7 .. 21.0 17.0 11.0 26.0 35.0 6.0 Central African Republic 15.3 .. 31.0 26.0 26.0 30.0 30.0 22.0 Chad 20.3 .. 37.0 37.0 30.0 38.0 48.0 29.0 Congo 13.2 .. 15.0 14.0 10.0 18.0 19.0 5.0 Democratic Republic of the Congo 18.5 .. 33.0 30.0 24.0 36.0 34.0 20.0 Equatorial Guinea .. .. 19.0 18.0 15.0 21.0 .. .. Gabon 6.6 .. 13.0 11.0 10.0 17.0 .. .. Sao Tome and Principe .. .. 9.0 9.0 8.0 11.0 13.0 5.0
  • 138. 126 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A6 (cont.) Share of adult Share of children population with CED underweight (% of total) (% of total) By sex By residence By household wealth quintile Women Men Male Female Urban Rural Poorest Richest Northern Africa 10.3 9.7 5.3 8.0 16.8 8.0 Algeria .. .. 4.0 4.0 3.0 4.0 5.0 3.0 Egypt 1.6 3.2 8.0 7.0 7.0 8.0 9.0 7.0 Libyan Arab Jamahiriya .. .. 5.0 4.0 4.0 6.0 .. .. Morocco (C) 7.3 5.7 10.0 10.0 7.0 14.0 17.0 4.0 Sudan .. .. 32.0 30.0 .. .. 36.0 18.0 Tunisia .. .. 3.0 3.0 .. .. .. .. Western Sahara .. .. .. .. .. .. .. .. Southern Africa 7.8 14.4 14.2 12.0 15.2 Botswana .. .. 13.0 13.0 12.0 14.0 .. .. Lesotho 5.7 .. 19.0 21.0 16.0 20.0 27.0 11.0 Namibia 15.9 .. 21.0 21.0 15.0 25.0 27.0 9.0 South Africa 6.2 12.5 13.0 11.0 12.0 11.0 .. .. Swaziland 3.2 10.1 6.0 5.0 5.0 6.0 8.0 4.0 Western Africa 12.9 27.1 25.8 17.7 28.1 32.4 15.8 Benin 9.2 .. 24.0 21.0 18.0 25.0 .. .. Burkina Faso 20.8 .. 38.0 37.0 26.0 41.0 44.0 24.0 Cape Verde (1) .. .. .. .. 9.0 9.0 .. .. Côte d’Ivoire 8.2 .. 22.0 19.0 13.0 24.0 26.0 10.0 Gambia .. .. 21.0 20.0 15.0 23.0 26.0 14.0 Ghana (C) 8.6 16.2 18.0 17.0 12.0 21.0 25.0 8.0 Guinea 13.2 .. 27.0 26.0 20.0 29.0 30.0 24.0 Guinea-Bissau .. .. 19.0 20.0 13.0 22.0 21.0 10.0 Liberia 10.0 .. 25.0 23.0 21.0 25.0 27.0 18.0 Mali 13.5 .. 33.0 31.0 .. .. .. .. Mauritania 13.0 .. 31.0 29.0 20.0 37.0 40.0 13.0 Niger 19.2 .. 45.0 44.0 27.0 47.0 48.0 30.0 Nigeria 12.2 .. 29.0 28.0 22.0 32.0 35.0 13.0 Saint Helena .. .. .. .. .. .. .. .. Senegal 18.2 .. 16.0 18.0 10.0 22.0 26.0 6.0 Sierra Leone 11.2 .. 32.0 29.0 23.0 33.0 36.0 21.0 Togo 10.9 .. 27.0 25.0 16.0 32.0 37.0 15.0 ASIA EXCLUDING JAPAN 13.3 15.6 19.4 14.7 19.5 Central Asia 6.9 8.6 7.8 7.4 8.4 9.6 5.2 Kazakhstan 7.4 .. 4.0 4.0 3.0 5.0 5.0 1.0 Kyrgyzstan 4.2 3.2 4.0 3.0 3.0 3.0 3.0 3.0 Tajikistan .. .. 18.0 17.0 17.0 17.0 22.0 14.0
  • 139. S t a t is t ic a l a n n ex 127 TABLE A6 (cont.) Share of adult Share of children population with CED underweight (% of total) (% of total) By sex By residence By household wealth quintile Women Men Male Female Urban Rural Poorest Richest Turkmenistan 9.9 .. 12.0 10.0 9.0 12.0 12.0 5.0 Uzbekistan 5.9 3.8 5.0 5.0 5.0 5.0 6.0 3.0 Eastern Asia excluding Japan 6.3 6.0 4.0 8.0 China (C) 8.5 9.2 .. .. 2.0 9.0 .. .. China, Hong Kong SAR .. .. .. .. .. .. .. .. China, Macao SAR .. .. .. .. .. .. .. .. China, mainland .. .. .. .. .. .. .. .. Democratic People’s Republic of Korea (2) .. .. 24.0 23.0 .. .. .. .. Mongolia 3.9 5.9 6.0 7.0 6.0 7.0 8.0 4.0 Republic of Korea 6.5 2.8 .. .. .. .. .. .. Southeastern Asia 18.2 14.1 25.3 25.3 23.4 30.4 Brunei Darussalam .. .. .. .. .. .. .. .. Cambodia 16.1 .. 35.0 36.0 35.0 36.0 43.0 23.0 Indonesia .. .. .. .. 25.0 30.0 .. .. Lao People’s Democratic Republic 14.8 12.1 37.0 38.0 26.0 39.0 44.0 18.0 Malaysia 10.0 9.2 19.0 19.0 16.0 23.0 .. .. Myanmar .. .. 31.0 32.0 25.0 34.0 .. .. Philippines 14.2 10.6 .. .. .. .. .. .. Singapore 14.6 4.4 4.0 3.0 .. .. .. .. Thailand 9.6 11.6 9.0 10.0 6.0 11.0 15.0 4.0 Timor-Leste 37.7 26.4 46.0 45.0 42.0 48.0 18.0 10.0 Viet Nam 28.3 24.4 21.0 19.0 12.0 22.0 29.0 10.0   Southern Asia 23.8 32.9 33.4 30.3 39.3 Afghanistan (1) .. .. 38.0 40.0 47.0 50.0 .. .. Bangladesh 29.7 .. 44.0 49.0 40.0 48.0 56.0 32.0 Bhutan .. .. 20.0 17.0 .. .. .. .. India 35.6 33.7 46.0 49.0 38.0 51.0 61.0 25.0 Iran (Islamic Republic of) 5.4 6.0 12.0 10.0 10.0 14.0 .. .. Maldives .. .. 31.0 30.0 .. .. .. .. Nepal 24.4 .. 38.0 40.0 23.0 41.0 47.0 19.0 Pakistan 31.6 30.8 38.0 36.0 35.0 39.0 .. .. Sri Lanka (3) 16.2 .. 29.0 30.0 19.0 32.0 .. .. Western Asia 11.4 11.1 Armenia 5.2 .. 2.0 6.0 4.0 4.0 5.0 1.0 Azerbaijan 4.8 2.1 9.0 10.0 6.0 13.0 17.0 4.0 Bahrain .. .. 7.0 11.0 .. .. .. .. Cyprus 6.9 1.7 .. .. .. .. .. ..
  • 140. 128 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A6 (cont.) Share of adult Share of children population with CED underweight (% of total) (% of total) By sex By residence By household wealth quintile Women Men Male Female Urban Rural Poorest Richest Georgia .. .. 2.0 2.0 2.0 3.0 3.0 2.0 Iraq .. .. 8.0 7.0 7.0 8.0 .. .. Israel .. .. .. .. .. .. .. .. Jordan 3.9 .. 4.0 5.0 4.0 7.0 .. .. Kuwait 2.3 2.7 10.0 9.0 .. .. .. .. Lebanon .. .. .. .. .. .. .. .. Occupied Palestinian Territory .. .. 3.0 3.0 3.0 3.0 .. .. Oman .. .. 18.0 18.0 .. .. .. .. Qatar (2) .. .. 7.0 5.0 .. .. .. .. Saudi Arabia 4.9 5.9 17.0 12.0 .. .. .. .. Syrian Arab Republic .. .. 11.0 9.0 9.0 10.0 13.0 8.0 Turkey (C) 1.6 1.5 .. .. 2.0 5.0 .. .. United Arab Emirates 10.0 .. 16.0 13.0 .. .. .. .. Yemen 25.2 .. 46.0 45.0 37.0 48.0 .. .. LATIN AMERICA AND THE CARIBBEAN Caribbean Anguilla .. .. .. .. .. .. .. .. Antigua and Barbuda .. .. .. .. .. .. .. .. Aruba .. .. .. .. .. .. .. .. Bahamas .. .. .. .. .. .. .. .. Barbados 3.3 3.1 .. .. .. .. .. .. British Virgin Islands .. .. .. .. .. .. .. .. Cayman Islands .. .. .. .. .. .. .. .. Cuba 6.2 5.3 .. .. 4.0 5.0 .. .. Dominica .. .. .. .. .. .. .. .. Dominican Republic 5.1 .. 4.0 4.0 4.0 5.0 7.0 2.0 Grenada .. .. .. .. .. .. .. .. Guadeloupe .. .. .. .. .. .. .. .. Haiti 15.5 .. 22.0 22.0 15.0 26.0 27.0 8.0 Jamaica .. .. 4.0 4.0 .. 5.0 .. .. Martinique .. .. .. .. .. .. .. .. Montserrat .. .. .. .. .. .. .. .. Netherlands Antilles .. .. .. .. .. .. .. .. Puerto Rico .. .. .. .. .. .. .. .. Saint Kitts & Nevis .. .. .. .. .. .. .. .. Saint Lucia .. .. .. .. .. .. .. .. Saint Vincent and the Grenadines .. .. .. .. .. .. .. .. Trinidad & Tobago .. .. 7.0 5.0 .. .. .. .. Turks and Caicos Islands .. .. .. .. .. .. .. .. United States Virgin Islands .. .. .. .. .. .. .. ..
  • 141. S t a t is t ic a l a n n ex 129 TABLE A6 (cont.) Share of adult Share of children population with CED underweight (% of total) (% of total) By sex By residence By household wealth quintile Women Men Male Female Urban Rural Poorest Richest Central America 2.9 9.8 9.9 6.9 12.9 Belize .. .. 5.0 7.0 4.0 8.0 .. .. Costa Rica (2) .. .. 6.0 4.0 4.0 7.0 .. .. El Salvador .. .. 10.0 11.0 7.0 13.0 .. .. Guatemala (3) 2.0 .. 23.0 23.0 16.0 26.0 .. .. Honduras 4.0 .. 11.0 12.0 6.0 15.0 22.0 2.0 Mexico 1.4 1.5 8.0 7.0 6.0 12.0 .. .. Nicaragua 3.7 .. 7.0 7.0 5.0 9.0 11.0 2.0 Panama 3.6 2.6 8.0 8.0 .. .. .. .. South America 7.2 6.9 5.4 9.9 Argentina (1) 3.4 .. .. .. .. .. .. .. Bolivia (Plurinational State of) 2.0 .. 6.0 6.0 4.0 9.0 .. .. Brazil (C) 3.5 2.8 6.0 5.0 5.0 9.0 .. .. Chile (2) 1.1 0.6 .. .. .. .. .. .. Colombia (3) 3.9 3.7 7.0 7.0 6.0 10.0 12.0 3.0 Ecuador .. .. 9.0 10.0 8.0 11.0 .. .. Falkland Islands (Malvinas) .. .. .. .. .. .. .. .. French Guiana .. .. .. .. .. .. .. .. Guyana .. .. 14.0 13.0 10.0 15.0 .. .. Paraguay .. .. 5.0 3.0 3.0 6.0 9.0 0.0 Peru 1.9 .. 6.0 5.0 2.0 9.0 12.0 1.0 Suriname .. .. 10.0 10.0 .. .. 12.0 8.0 Uruguay .. .. 4.0 5.0 .. .. .. .. Venezuela (Bolivarian Republic of) .. .. 5.0 5.0 .. .. .. ..   OCEANIA EXCLUDING AUSTRALIA AND NEW ZEALAND American Samoa 0.2 .. .. .. .. .. .. .. Cook Islands .. .. .. .. .. .. .. .. Fiji 5.6 6.6 .. .. .. .. .. .. French Polynesia .. .. .. .. .. .. .. .. Guam .. .. .. .. .. .. .. .. Kiribati 0.6 0.3 .. .. .. .. .. .. Marshall Islands .. .. .. .. .. .. .. .. Micronesia (Federated States of) .. .. .. .. .. .. .. .. Nauru .. .. .. .. .. .. .. .. New Caledonia .. .. .. .. .. .. .. .. Niue .. .. .. .. .. .. .. .. Northern Mariana Islands .. .. .. .. .. .. .. .. Palau .. .. .. .. .. .. .. .. Papua New Guinea (1) .. .. 28.0 25.0 18.0 28.0 .. .. Samoa .. .. .. .. .. .. .. ..
  • 142. 130 TH E S TAT E O F F O O D AN D A G R I C U L T U R E 2 0 1 0 – 1 1 TABLE A6 (cont.) Share of adult Share of children population with CED underweight (% of total) (% of total) By sex By residence By household wealth quintile Women Men Male Female Urban Rural Poorest Richest Solomon Islands .. .. .. .. .. .. .. .. Tokelau .. .. .. .. .. .. .. .. Tonga .. .. .. .. .. .. .. .. Tuvalu .. .. .. .. .. .. .. .. Vanuatu 2.9 1.0 18.0 13.0 15.0 16.0 18.0 13.0 Wallis and Futuna Islands .. .. .. .. .. .. .. .. COUNTRIES IN DEVELOPED REGIONS ASIA AND OCEANIA 5.1 2.3 Australia 2.8 1.3 .. .. .. .. .. .. Japan 10.8 4.3 .. .. .. .. .. .. New Zealand 1.6 1.3 .. .. .. .. .. .. EUROPE Eastern Europe 4.9 1.1 Belarus .. .. 1.0 1.0 1.0 2.0 2.0 1.0 Bulgaria 5.9 1.6 .. .. .. .. .. .. Czech Republic 3.7 1.0 .. .. .. .. .. .. Czechoslovakia .. .. .. .. .. .. .. .. Hungary 3.0 0.4 .. .. .. .. .. .. Poland 3.2 1.0 .. .. .. .. .. .. Republic of Moldova 5.9 .. 3.0 5.0 3.0 5.0 7.0 1.0 Romania 4.8 1.1 3.0 3.0 3.0 3.0 .. .. Russian Federation .. .. 3.0 3.0 .. .. .. .. Slovakia 7.4 1.6 .. .. .. .. .. .. Ukraine (4) 5.4 .. 1.0 1.0 .. .. .. .. USSR .. .. .. .. .. .. .. .. Yugoslav SFR .. .. .. .. .. .. .. .. Northern Europe 3.9 1.7 Denmark 3.7 0.8 .. .. .. .. .. .. Estonia 4.4 1.3 .. .. .. .. .. .. Faroe Islands .. .. .. .. .. .. .. .. Finland 3.1 1.6 .. .. .. .. .. .. Iceland 3.0 1.6 .. .. .. .. .. .. Ireland 1.0 2.0 .. .. .. .. .. .. Latvia 5.3 1.2 .. .. .. .. .. .. Lithuania 3.0 1.6 .. .. .. .. .. .. Norway 7.0 2.0 .. .. .. .. .. ..
  • 143. S t a t is t ic a l a n n ex 131 TABLE A6 (cont.) Share of adult Share of children population with CED underweight (% of total) (% of total) By sex By residence By household wealth quintile Women Men Male Female Urban Rural Poorest Richest Sweden 3.0 1.0 .. .. .. .. .. .. United Kingdom 5.9 4.1 .. .. .. .. .. .. Southern Europe Albania .. .. 8.0 7.0 5.0 9.0 13.0 3.0 Andorra .. .. .. .. .. .. .. .. Bosnia and Herzegovina .. .. 2.0 1.0 2.0 1.0 3.0 2.0 Croatia 0.2 0.1 .. .. .. .. .. .. Gibraltar .. .. .. .. .. .. .. .. Greece .. .. .. .. .. .. .. .. Holy See .. .. .. .. .. .. .. .. Italy 5.8 0.9 .. .. .. .. .. .. Malta 3.8 1.3 .. .. .. .. .. .. Montenegro .. .. 4.0 2.0 3.0 2.0 6.0 2.0 Portugal 3.4 0.9 .. .. .. .. .. .. San Marino .. .. .. .. .. .. .. .. Serbia .. .. 2.0 2.0 2.0 1.0 4.0 2.0 Serbia and Montenegro .. .. .. .. .. .. .. .. Slovenia .. .. .. .. .. .. .. .. Spain 3.0 0.5 .. .. .. .. .. .. The former Yugoslav Republic of Macedonia 6.4 .. 2.0 2.0 2.0 2.0 4.0 1.0 Western Europe Austria 4.0 1.0 .. .. .. .. .. .. Belgium 5.3 2.6 .. .. .. .. .. .. Belgium-Luxembourg .. .. .. .. .. .. .. .. France .. .. .. .. .. .. .. .. Germany .. .. .. .. .. .. .. .. Liechtenstein .. .. .. .. .. .. .. .. Luxembourg .. .. .. .. .. .. .. .. Monaco .. .. .. .. .. .. .. .. Netherlands .. .. .. .. .. .. .. .. Switzerland 5.9 1.0 .. .. .. .. .. .. NORTHERN AMERICA 3.7 1.4 Bermuda .. .. .. .. .. .. .. .. Canada 4.1 1.2 .. .. .. .. .. .. Greenland .. .. .. .. .. .. .. .. Saint Pierre and Miquelon .. .. .. .. .. .. .. .. United States of America (5) 3.3 1.5 2.0 1.0 .. .. .. ..
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  • 158. 146 Special chapters of The State of Food and Agriculture In addition to the usual review of the recent world food and agricultural situation, each issue of this report since 1957 has included one or more special studies on problems of longer-term interest. Special chapters in earlier issues have covered the following subjects: 1957 Factors influencing the trend of food consumption Postwar changes in some institutional factors affecting agriculture 1958 Food and agricultural developments in Africa south of the Sahara The growth of forest industries and their impact on the world’s forests 1959 Agricultural incomes and levels of living in countries at different stages of economic development Some general problems of agricultural development in less-developed countries in the light of postwar experience 1960 Programming for agricultural development 1961 Land reform and institutional change Agricultural extension, education and research in Africa, Asia and Latin America 1962 The role of forest industries in the attack on economic underdevelopment The livestock industry in less-developed countries 1963 Basic factors affecting the growth of productivity in agriculture Fertilizer use: spearhead of agricultural development 1964 Protein nutrition: needs and prospects Synthetics and their effects on agricultural trade 1966 Agriculture and industrialization Rice in the world food economy 1967 Incentives and disincentives for farmers in developing countries The management of fishery resources 1968 Raising agricultural productivity in developing countries through technological improvement Improved storage and its contribution to world food supplies 1969 Agricultural marketing improvement programmes: some lessons from recent experience Modernizing institutions to promote forestry development 1970 Agriculture at the threshold of the Second Development Decade 1971 Water pollution and its effects on living aquatic resources and fisheries 1972 Education and training for development Accelerating agricultural research in the developing countries 1973 Agricultural employment in developing countries 1974 Population, food supply and agricultural development 1975 The Second United Nations Development Decade: mid-term review and appraisal 1976 Energy and agriculture 1977 The state of natural resources and the human environment for food and agriculture 1978 Problems and strategies in developing regions 1979 Forestry and rural development 1980 Marine fisheries in the new era of national jurisdiction 1981 Rural poverty in developing countries and means of poverty alleviation 1982 Livestock production: a world perspective 1983 Women in developing agriculture 1984 Urbanization, agriculture and food systems
  • 159. 147 1985 Energy use in agricultural production Environmental trends in food and agriculture Agricultural marketing and development 1986 Financing agricultural development 1987–88 Changing priorities for agricultural science and technology in developing countries 1989 Sustainable development and natural resource management 1990 Structural adjustment and agriculture 1991 Agricultural policies and issues: lessons from the 1980s and prospects for the 1990s 1992 Marine fisheries and the law of the sea: a decade of change 1993 Water policies and agriculture 1994 Forest development and policy dilemmas 1995 Agricultural trade: entering a new era? 1996 Food security: some macroeconomic dimensions 1997 The agroprocessing industry and economic development 1998 Rural non-farm income in developing countries 2000 World food and agriculture: lessons from the past 50 years 2001 Economic impacts of transboundary plant pests and animal diseases 2002 Agriculture and global public goods ten years after the Earth Summit 2003–04 Agricultural biotechnology: meeting the needs of the poor? 2005 Agriculture trade and poverty: can trade work for the poor? 2006 Food aid for food security? 2007 Paying farmers for environmental services 2008 Biofuels: prospects, risks and opportunities 2009 Livestock in the balance
  • 160. THE STATE OF FOOD AND AGRICULTURE Women make significant contributions to the rural economy in all developing country regions. Their roles differ across regions, yet they consistently have less access than men to the resources and opportunities they need to be more productive. Increasing women’s access to land, livestock, education, financial services, extension, technol- ogy and rural employment would boost their productivity and generate gains in terms of agricultural production, food security, economic growth and social welfare. Closing the gender gap in agricultural inputs alone could lift 100–- 150 million people out of hunger. No blueprint exists for closing the gender gap, but some basic principles are universal: governments, the international community and civil society should work together to eliminate discrimina- tion under the law, to promote equal access to resources and opportunities, to ensure that agricultural policies and programmes are gender-aware, and to make women’s voices heard as equal partners for sustainable develop- ment. Achieving gender equality and empowering women in agriculture is not only the right thing to do. It is also crucial for agricultural development and food security. ISBN 978-92-5-106768-0 ISSN 0081-4539 9 789251 067680 I2050E/1/01.11