Proxy Means Testing Vulnerability to Measurement Errors ?
Jules Gazeaud
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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 random measurement errors – an assumption that has been challenged by recent literature. Using a survey experiment conducted in Tanzania, this paper brings causal evidence on the impact of non-random errors on PMT performances. Results show that non-random errors bias the coefficients from PMT models, resulting in a 5 to 27 per cent reduction in PMT predictive performances. Moreover, non-random errors induce a 10 to 34 per cent increase in the incidence of targeting errors when poverty is defined in absolute terms. More reassuringly, impacts on the ranking of households are smaller and essentially non-significant. Taken together, these results indicate that PMT performances are quite vulnerable to non-random errors when the objective is to target absolutely poor households, but remain largely unaffected when the objective is to target a fixed share of the population.
Keywords: Social protection; Targeting; Proxy Means Testing PMT; Measurement errors (search for similar items in EconPapers)
Date: 2020-11-01
New Economics Papers: this item is included in nep-dev
Note: View the original document on HAL open archive server: https://uca.hal.science/hal-03157274v1
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Citations: View citations in EconPapers (2)
Published in The Journal of Development Studies, 2020, 56 (11), pp.2113-2133. ⟨10.1080/00220388.2020.1715942⟩
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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? (2018) 
Working Paper: Proxy Means Testing vulnerability to measurement errors? (2018) 
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03157274
DOI: 10.1080/00220388.2020.1715942
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