Estimating poverty among refugee populations: a cross-survey imputation exercise for Chad

Abstract

ABSTRACT Household consumption surveys do not typically offer poverty estimates for refugees. We test the performance of a recently developed cross-survey imputation method to estimate poverty for a sample of refugees in Chad, combining survey and administrative data collected by the United Nations High Commissioner for Refugees (UNHCR). We find the imputed poverty rates are not statistically different from the poverty rates obtained directly from the survey consumption data. This result is robust to different model specifications, varying poverty lines, and assumptions of the error terms. Targeting results based on the imputed poverty estimates also outperform common targeting methods, such as proxy means tests and the current targeting method used by humanitarian organizations in Chad. Replicating this approach in at least some of the 122 other countries currently using UNHCR administrative data could help address data gaps and provide much-needed estimates to effectively respond to forcibly displaced crises.