Proxy Means Testing vulnerability to measurement errors?

Jules Gazeaud

CERDI Working papers from HAL

Abstract: Proxy Means Testing (PMT) is a popular method to target the poor in developing countries. PMT usually relies on survey-based consumption data and assumes they are measured with random errors – an assumption that has been challenged by recent literature. This paper brings causal evidence on the impact of non-random errors on PMT performances. Using a survey experiment conducted in Tanzania in which eight alternative consumption questionnaires were randomly distributed across households, I compare the performances of PMT relying on error-prone consumption data with those of a PMT using gold standard consumption data. Results show that non-random errors reduce the predictive performances of PMT by a magnitude ranging from 5 to 27 percent, which in turn induce a 10 to 34 percent increase in the incidence of targeting errors (using the typical PPP $1.25 poverty line). Impacts on the relative distribution of households are nonetheless small and non-significant.

Keywords: Social protection; Targeting; Proxy Means Testing (PMT); Measurement errors (search for similar items in EconPapers)
Date: 2018-10-04
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01887649
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Related works:
Journal Article: Proxy Means Testing Vulnerability to Measurement Errors? (2020)
Working Paper: Proxy Means Testing Vulnerability to Measurement Errors ? (2020)
Working Paper: Proxy Means Testing vulnerability to measurement errors? (2018)
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