Weighty Evidence? Poverty Estimation with Missing Data

Jean Drèze and Anmol Somanchi

Studies in Microeconomics, 2024, vol. 12, issue 1, 93-106

Abstract: Attempts have been made to estimate poverty in India using a biased dataset, by adjusting household weights to remove or reduce the bias. The effectiveness of this method, however, is uncertain. Simulation exercises suggest that its ability to correct poverty estimates varies wildly depending on the nature of the underlying bias, which may be hard to guess—there lies the rub. When the bias changes over time, estimating poverty trends becomes truly problematic. There are wider lessons for poverty estimation with biased or missing data. JEL Classifications: C83, I32

Keywords: India; poverty estimation; missing data; max-entropy (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:miceco:v:12:y:2024:i:1:p:93-106

DOI: 10.1177/23210222241238846

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