Targeting Impact versus Deprivation

A large literature has examined how best to target antipoverty programs to those most deprived in some sense (e.g., consumption). We examine the potential trade-off between this objective and targeting those most impacted by such programs. We work in the context of an NGO cash transfer program in Kenya, employing recent advances in machine learning methods and dynamic outcome data to learn proxy means tests that jointly target both objectives. Targeting solely on the basis of deprivation is not attractive in this setting under standard social welfare criteria unless the planner’s preferences are extremely redistributive. (JEL C45, D63, I31, I38, L31, O15)

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Publication Details

Journal
American Economic Review
Published
2025-05-30
DOI
https://doi.org/10.1257/aer.20221650
Citations
5
Primary Topic
Poverty, Education, and Child Welfare
Type
article
Field-Weighted Citation Impact
11.83
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article

Targeting Impact versus Deprivation

Michael Walker, Johannes Haushofer, Paul Niehaus, Edward Miguel et al.
5 citations
American Economic Review
Poverty, Education, and Child Welfare
11.83
article

Targeting Impact versus Deprivation

Michael Walker, Johannes Haushofer, Paul Niehaus, Edward Miguel, Carlos Paramo
article en
5 citations

Abstract

A large literature has examined how best to target antipoverty programs to those most deprived in some sense (e.g., consumption). We examine the potential trade-off between this objective and targeting those most impacted by such programs. We work in the context of an NGO cash transfer program in Kenya, employing recent advances in machine learning methods and dynamic outcome data to learn proxy means tests that jointly target both objectives. Targeting solely on the basis of deprivation is not attractive in this setting under standard social welfare criteria unless the planner’s preferences are extremely redistributive. (JEL C45, D63, I31, I38, L31, O15)

American Economic ReviewVol. 115(6)
Cornell University (US), University of California San Diego (US), Center for Effective Global Action (US), Brooks Automation (Germany) (DE), University of California, Berkeley (US)
Openalex Percentile: Top 2%
Poverty, Education, and Child Welfare
11.83
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