Full Citation

Title: Adaptive Safety Nets for Rural Africa: Drought-sensitive targeting with sparse data

Citation Type: Working Paper

Publication Year: 2019

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Abstract: This paper combines remote-sensed data and individual child-, mother-, and household-level data from the Demographic and Health Surveys for five countries in Sub-Saharan Africa (Malawi, Tanzania, Mozambique, Zambia, and Zimbabwe) to design a prototype drought-contingent targeting framework that may be used in scarce-data contexts. To accomplish this, the paper: (i) develops simple and easy-to-communicate measures of drought shocks; (ii) shows that droughts have a large impact on child stunting in these five countries—comparable, in size, to the effects of mother’s illiteracy and a fall to a lower wealth quintile; and (iii) shows that, in this context, decision trees and logistic regressions predict stunting as accurately (out-of-sample) as machine learning methods that are not interpretable. Taken together, the analysis lends support to the idea that a datadriven approach may contribute to the design of policies that mitigate the impact of climate change on the world’s most vulnerable populations.

Url: https://elibrary.worldbank.org/doi/pdf/10.1596/1813-9450-9071

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Authors: Baez, Javier E; Kshirsagar, Varun; Skoufias, Emmanuel

Series Title: Policy Research Working Paper

Publication Number: 9071

Institution: World Bank Group

Pages: 1-57

Publisher Location:

Data Collections: IPUMS Global Health - DHS

Topics: Family and Marriage, Health, Natural Resource Management

Countries: Malawi, Mozambique, Tanzania, Zambia, Zimbabwe