‘Human Capital and Water: Assessing the direct relationship and the impact of urban dimensions’, Presentation by Sylvia Szabo, Social Statistics & Demography, University of Southampton. Multidisciplinary Research Week 2013. #MDRWeek.

‘Human Capital and Water: Assessing the direct relationship and the impact of urban dimensions’, Presentation by Sylvia Szabo, Social Statistics & Demography, University of Southampton. Multidisciplinary Research Week 2013. #MDRWeek.

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  World Water Day:Water Cooperation Multidisciplinary Research Week 2013 ‘Human Capital and Water: Assessing the direct relationship and the impact of urban dimensions’, By Sylvia Szabo, Social Statistics & Demography, University of Southampton.
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  Human Capital andWater Assessing the direct relationship and the impact of urban dimensions Sylvia Szabo, Social Statistics & Demography ([email protected]) Multi-disciplinary Research Week
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  Motivation • Malthusian, neo-Malthusian& counter arguments (Ehrlich, Boserup, Simon, Cohen); • Current state of access to safe drinking water; • Emerging urban challenges and opportunities; • Systematic regional, global studies limited • Reliable household level data available (e.g. DHS).
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  The global watersituation • The target of halving the proportion of people without SDR was met; • However challenges remain, in particular in SSA
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  Urbanization in developingcountries • Globally 53% urban; projected to increase to 67% by 2050; • Megacities, with population of at least 10 million growing rapidly. Currently, 23 megacities; projected to 37 by 2025; • Urban growth, often uncontrolled and unplanned; • Serious threats to public health, sanitation and environment • Inequity and inequality in human development, with increasing migration of the poor
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  Urbanization impact • Overallurbanisation likely to have positive effect on access to education and as such it stimulates human capital accumulation; • However: growth of slums, poor access to water, poor sanitation and greater burden of disease make children more disadvantaged (education and health); • Rapid urban growth both a challenge and an opportunity, can positively and/or negatively impact the association between human capital and water access.
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  Research hypotheses H1: Thereis a positive independent association between human capital and access to improved water sources. H2: Level of urbanization influences the magnitude and direction of the association between human capital and water access. H3: The magnitude of the association between human capital and access to water varies depending on countries’ level of development.
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  Macro-level HC- SDWassociation (LDCs vs. non-LDCs) Association between education and access to improved water sources by level of development 100 Qatar Lebanon Singapore Barbados GreeceAustria Uruguay United CyprusItaly Finland Hungary Ireland Australia Czech Republic TFYR MacedoniaArab Emirates (UAE) Belgium NetherlandsGermany Malaysia Luxembourg Belarus Malta France Switzerland Sweden NewNorway Spain Tonga Iceland Bulgaria DenmarkIsrael Japan Slovakia Canada Zealand Kuwait Egypt Turkey Mauritius Portugal Bosnia-Hercegovina Croatia Serbia Slovenia Latvia U.S.A Maldives Fiji MontenegroRepublicEstonia Ukraine of Korea Georgia Brazil Costa Rica Jordan Russian Federation Armenia Thailand Belize Botswana Chile Albania Comoros Iran Moldova Samoa Kazakhstan Tunisia Ecuador Mexico Trinidad and Tobago Cuba Marshall Islands Guyana Panama Jamaica Access to improved water source Guatemala Vietnam Colombia Suriname Namibia Philippines Lithuania Pakistan South Africa India Kyrgyzstan Gambia Sao Tome and Principle Syria China Sri Lanka Romania Nepal Djibouti Oman Cape Verde Honduras Gabon El Salvador Uzbekistan Dominican Republic Paraguay Bolivia Nicaragua Palau Peru Algeria 80 Morocco Ghana Bangladesh Indonesia Mongolia Myanmar Zimbabwe Cote d'Ivoire Malawi IraqLesotho Burkina-Faso Cameroon Benin Guinea Burundi Liberia Congo (Brazzaville) Senegal Uganda Haiti Central African Republic Timor-Leste Rwanda Swaziland Laos Tajikistan 60 Guinea Bissau Mali Togo Cambodia Zambia Sudan Nigeria Kenya Yemen Sierra Leone Tanzania Chad Afghanistan Angola Niger Mauritania Mozambique Democratic Republic of theMadagascar Congo (DRC) 40 Ethiopia Papua New Guinea 20 2 4 6 8 10 12 14 Mean years of schooling LDC non-LDC 8
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  Conceptual framework • Motivatedby the Sustainable Livelihoods Framework (inspired by works of Amartya Sen & Institute of Development Studies); - Conceptual factors (vulnerability aspect) affect initial livelihood resources/capital (financial, human, social) - Available capital Livelihood strategies & mitigating factors Livelihood outcomes • Complemented by literature/policy sources in the area of world development (FAO, WB, WHO).
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  Conceptual framework
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  Data & methods •Database of 35 DHS countries (including 19 LDCs and 16 non-LDCs) – More than half million cases (households) • Descriptive statistics and multilinear logistic regression • Key variables: – Safe/unsafe water (UN classification); – Human capital (mean years of education of hh members in working ages); – Place of residence (urban/rural); – Contextual urban variables (urban growth, proportion of urban population, urban population residing in slums).
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  Does human capitalincrease the odds to access water? Predicted odds of access to improved water source 10 8 Predicted odds 6 4 2 0 5 10 15 Household education 12
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  Urban impact Predicted odds of access to improved water source by urban dimensions 12 10 10 8 Predicted odds 8 6 6 4 4 2 2 1.5 2 2.5 3 3.5 4 4.5 5 rural urban Urban growth (%) 15 12 10 10 Predicted odds 8 6 5 4 2 0 15 25 35 45 55 65 75 15 25 35 45 55 65 75 Proportion urban (%) Urban population in slums (%) 13
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  Predicted odds ofaccess to improved water sources by urban dimensions (non-LDCs) 15 8 10 6 Predicted odds 4 5 2 Non-LDCs 0 0 rural urban 29 39 49 59 69 Proportion urban (%) 30 25 20 20 exp(xb()) Predicted odds 15 10 10 5 0 0 1.5 2 2.5 3 3.5 17 27 37 47 57 Urban growth (%) Urban population in slums (%) Predicted odds of access to improved water sources by urban dimensions (LDCs) 15 8 Predicted odds 10 6 4 5 2 0 0 rural urban 13 23 33 43 LDCs Proportion urban (%) 10 12 10 8 Predicted odds 8 6 6 4 4 2 2 14 0 2.8 3.2 3.6 4 4.4 38 48 58 68 78 Urban growth (%) Urban population in slums (%)
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  Conclusions & policyimplications (1) • Human capital has a significant positive impact on access to safe drinking water – This impact is greater in the LDCs • Urbanisation has a significant mitigating impact on the association between human capital and water access: – Differentiated in non-LDCs (positive impact of urban growth and proportion urban) – Negative in LDCs • HHs with female head of HH are more likely to have access to SDW, in particular in LDCs. 15
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  Conclusions and policyimplications (2) • Investments in human capital are crucial, in particular in the LDCs; • Sustained urbanisation and urban planning are indispensable in order for households to benefit from the positive impact of living in towns/cities; • Overall infrastructure and HHs’ distance to water source is key; • Gender differentials still exist, greater in LDCs - scale up investments in gender equality; • Integrated approach & multistakeholder collaboration. 16
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  World Water Day:Water Cooperation Multidisciplinary Research Week 2013 See the latest videos, interviews, pictures, tweets and views from the floor at: Website: www.southampton.ac.uk/multidisciplinary Blog: http://blog.soton.ac.uk/multidisciplinary/tag/mdrweek/ Youtube: Search #MDRWeek Follow us on Twitter @Multisoton #MDRWeek