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Poverty remains at very high levels in Mali with 43.6% of the population living in absolute poverty. The purpose of this study is to develop an improved method of targeting the poor in social protection programs based on Proxy-Based Means Testing (PMT) using the latest household survey data. Identifying the poor that should be targeted is particularly difficult if the majority of household live around the poverty line. We find that designing a PMT targeting scheme leads to relatively high inclusion and exclusion errors even if we consider a large number of household characteristics to predict consumption. Using an implementable PMT scheme based on quantile regressions and including only seven variables, 28% of the poor would not be covered whereas 24% of the resources would be targeted to non-poor households. The optimal coverage rate is found to be between 20 and 25 per cent of the population, and such a large-scale social protection programme could reduce extreme poverty by approximately 13 percentage points.
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