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Community Targeting for Poverty Reduction in Burkina Faso


  • David Bigman
  • Stefan Dercon
  • Dominique Guillaume
  • Michel Lambotte


The paper develops a method for targeting anti-poverty programs and public projects on poor communities in rural and urban areas. The method is based on the application of an extensive data-set from a large number of sources and the integration of the entire data-set in a Geographical Information System. This data-set includes data from the population census, household-level data from a variety of surveys, community-level data on the local road infrastructure, public facilities, water points, etc., and department-level data on the agro-climatic conditions. An econometric model that estimates the impact of household-, community-, and department-level variables on households’ consumption has been used to identify the key explanatory variables that determine the standard of living in rural and urban areas. This model was applied to predict poverty indicators for 3871 rural and urban communities across the country and to provide a mapping of the spatial distribution of poverty in Burkina Faso. Simulation analysis was subsequently conducted to assess the effectiveness of village-level targeting based on these predictions of the poverty indicators. The results show that village-level targeting based on these predictions provides an improvement over regional targeting by reducing the leakage of the targeted program and the percentage of the population that remains undercovered

Suggested Citation

  • David Bigman & Stefan Dercon & Dominique Guillaume & Michel Lambotte, 1999. "Community Targeting for Poverty Reduction in Burkina Faso," Working Papers Department of Economics ces9910, KU Leuven, Faculty of Economics and Business, Department of Economics.
  • Handle: RePEc:ete:ceswps:ces9910

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    Cited by:

    1. Nikos Tzavidis & Nicola Salvati & Monica Pratesi & Ray Chambers, 2008. "M-quantile models with application to poverty mapping," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(3), pages 393-411, July.
    2. Ravallion, Martin, 2000. "Monitoring Targeting Performance When Decentralized Allocations to the Poor Are Unobserved," World Bank Economic Review, World Bank Group, vol. 14(2), pages 331-345, May.
    3. Johannes Gräb & Michael Grimm, 2008. "Spatial Inequalities Explained: Evidence from Burkina Faso," Discussion Papers of DIW Berlin 843, DIW Berlin, German Institute for Economic Research.
    4. Jean-Pierre Lachaud, 2007. "La dynamique de pauvreté provinciale et le marché du travail à Madagascar. Une analyse fondée sur une décomposition de régression," Documents de travail 136, Groupe d'Economie du Développement de l'Université Montesquieu Bordeaux IV.
    5. Benjamin Davis, 2002. "Is it Possible to Avoid a Lemon? Reflections on Choosing a Poverty Mapping Method," Working Papers in Food Policy and Nutrition 08, Friedman School of Nutrition Science and Policy.

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