To estimate the effects of weather conditions on welfare globally, cross-country comparisons need to rely on international poverty lines and comparable data sources at the micro-level. To this end, nationally representative household surveys can offer a useful instrument, also at the sub-national level. This study seeks to expand the existing knowledge on the determinants of poverty in Africa south of the Sahara (SSA), examining how long-term climatic conditions and year-specific weather shocks affect expenditure per capita. We take advantage of a novel and unique dataset combining consumption-based household surveys for 24 SSA countries -representative of more than half of the African population and two thirds of SSA- and geospatial information on agro-climatic conditions, market access and other spatial covariates of poverty. To our knowledge, it is the first time that a welfare-based, multidisciplinary, micro-level dataset with such wide spatial coverage has been assembled and examined. Our analysis relies on a linear and spatial model at the household- and district-level, respectively, both controlling for socio-economic, demographic, and geographic confounding factors. Results are consistent across econometric approaches, showing that living in more humid areas is positively associated with welfare, while the opposite occurs living in hotter areas, as existing literature shows. Flood shocks -defined as annual rainfall higher than one standard deviation from the 50-year average- are associated to a 35% decrease in total and food per-capita consumption and 17 percentage point increase in extreme poverty. On the other hand, extreme shortages of rain and heat shocks show an uncertain effect, even when estimates control for spatial correlation between welfare and weather conditions using the spatial error correction model. Given the heterogeneous effects of climatic events across SSA macro-regions, local-specific adaptation and mitigation strategies are suggested to help bringing households on a sustainable path.
Keywords: Climate change; Mapping; Poverty; Spatial models; Sub-Saharan Africa; Weather shocks.
© 2019 The Authors.