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© 2000 International Bank for Reconstruction and Development / The World Bank

research-article

Community Targeting for Poverty Reduction in Burkina Faso

David Bigman, Stefan Dercon, Dominique Guillaume, and Michel Lambotte

the International Service for National Agricultural Research the Netherlands d.bigman{at}cgiar.org
the Department of Economics at the Catholic University of Leuven Belgium and the Centre for the Study of African Economies at Oxford University stefan.dercon{at}econ.kuleuven.ac.be
the African Department at the International Monetary Fund dguillaume{at}imf.org
I-Mage, a consulting group based in Belgium info@i-mage.be

This article develops a method for targeting antipoverty programs and public projects to poor communities in rural and urban areas. The method calls for constructing an extensive data set from a large number of sources and then integrating the entire set into a geographic information system. The data set includes demographic data from the population census; household-level data from a variety of surveys; community-level data on local road infrastructure, public facilities, water points, and so on; and department-level data on agroclimatic conditions. An econometric model that estimates the impact of household-, community-, and department-level variables on household consumption is used to identify the key explanatory variables that determine the standard of living in rural and urban areas. This model is then applied to predict poverty indicators for 3,871 rural and urban communities in Burkina Faso and to map the spatial distribution of poverty in the country. A simulation analysis assesses the effectiveness of village-level targeting based on these predictions. The results show that such targeting is an improvement over regional targeting in that it reduces leakage and undercoverage.


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