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Proxy Means Testing vulnerability to measurement errors?

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  • Jules Gazeaud

    (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique)

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.

Suggested Citation

  • Jules Gazeaud, 2018. "Proxy Means Testing vulnerability to measurement errors?," Working Papers halshs-01887649, HAL.
  • Handle: RePEc:hal:wpaper:halshs-01887649
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01887649
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    Cited by:

    1. Joachim De Weerdt, John Gibson and Kathleen Beegle, 2019. "What can we learn from experimenting with survey methods?," LICOS Discussion Papers 41819, LICOS - Centre for Institutions and Economic Performance, KU Leuven.

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    Keywords

    Measurement errors; Social protection; Targeting; Proxy Means Testing (PMT);

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