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The Complementarity of MDG Achievements: The Case of Child Mortality in Sub-Saharan Africa


Research Institutions:

IRD, DIAL, Paris, France and Kiel Institute, Kiel, Germany




The overall objective of this project is to analyze the determinants of child mortality with a focus on Millennium Development Goals (MDG) complementarities. More specifically, we examine how progresses in other MDGs, in particular the reduction of income poverty, the expansion of female education, and improved access to safe drinking water, affect child mortality. Knowledge about such ‘MDG complementarities’ can be used as an input into cost estimates of MDG achievement.

The analysis departs from the analytical framework for the study of child mortality proposed by Mosley and Chen that distinguishes between proximate and socio-economic determinants of child mortality. Proximate determinants are directly affecting child mortality risk and include maternal factors (age, parity, birth interval), environmental contamination (hygienic factors, water, sanitation), nutrition, injuries, and personal illness control. In contrast, all socio-economic variables, e.g. parental education and income/wealth as well as community health infrastructure, have to operate through these proximate determinants. For our empirical analysis, we have selected four country pairs from different Sub-Saharan regions. The pairs typically share some important characteristics, e.g. geographic and climatic conditions and/or income levels, but may differ in other dimensions, e.g. child mortality levels and changes therein, recent economic performance, or vaccination levels. These country pairs are Madagascar-Mozambique and Uganda-Kenya in East Africa and Senegal-Guinea and Mali-Niger in West Africa. Another criterion for country selection was the availability of at least two relatively recent Demographic and Health Surveys (DHS). We hence combine a microeconometric with a comparative cross-country approach.

For each country, we (1) estimate a survival model including a set of explanatory variables reflecting proximate and socio-economic determinants common to all surveys from all countries in all years – the estimates should inform us about major structural breaks over time and highlight possible differences in mortality patterns between the country-case studies; (2) estimate the same survival model using only the latest survey – this allows us to include information on a child’s vaccination status, which, unfortunately, is not available for earlier years; (3) estimate the influence of mothers’ educational attainment and income/wealth on proximate determinants (short birth interval) as well as on the use of public services, more specifically children’s vaccination status and the use of water from public taps – these estimations hence examine the transmission channels through which the possible complementarities between MDGs work. Finally, we want to (4) use the estimation results from 2 and 3 to simulate the effect of expanding mothers’ education, reducing income poverty and improving public health service delivery. These simulations based on hypothetical scenarios give an indication of the order of magnitude of the respective impacts on country-wide child mortality rates (as opposed to the effects on individual child survival probabilities).


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