A poor means test?
Proxy-means tests (PMTs) are popular for poverty-targeting with imperfect information. In a widely-used version, a regression for log consumption calibrates a PMT score based on covariates, which is then implemented for targeting out-of-sample. The performance of various PMT methods is assessed using data for nine African countries. Standard PMTs help filter out the non-poor, but exclude many poor people, thus diminishing the impact on poverty. Poverty-focused econometric methods such as using quantile regression generally do better. We also characterize the optimal informationally-feasible solution for poverty targeting and compare it to econometric methods. Even with a budget sufficient to eliminate poverty with full information, none of the targeting methods studied bring the poverty rate below about three-quarters of its initial value. The prevailing methods are particularly deficient in reaching the poorest. A basic-income scheme or transfers using a simple demographic scorecard often do as well, or even better, in reducing poverty.
