Community-Based versus Statistical Targeting of Anti-Poverty Programs: Evidence from Burkina Faso

Abstract

Abstract Targeting of governmental welfare programmes in low-income countries commonly relies on statistical procedures involving household-level data, while smaller-scale programmes often employ community-based targeting, where village communities themselves identify beneficiaries. Combining original data from community-based targeting exercises in Burkina Faso with a household survey we compare the targeting accuracy of community-based targeting with four common statistical targeting methods when the objective is to target consumption-poor households. We find that community-based targeting is substantially less accurate than statistical targeting in villages, while it is as accurate as the much more costly statistical methods in semi-urban areas. We show that this difference is due to differences in poverty concepts held by rural and urban communities. Its large cost advantage makes community-based targeting far more cost-effective than statistical targeting for common amounts of welfare programme benefits.