Heterogeneity in Effects of Poverty-Alleviating Interventions

To what extent are poverty-alleviating interventions general tools? We revisit a 415-village cluster-randomized field experiment involving 8,300 women living in poverty in rural Kenya. We estimate the extent of heterogeneity in a cash transfer intervention, an aspirations-improving workshop, and their combination using median split regressions and causal forests. We find no evidence of heterogeneity with respect to a prespecified set of demographic, psychological, and economic welfare characteristics. We conclude that the poverty-alleviating interventions we consider are general tools that can assist a broad range of households experiencing poverty and economic shocks.

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Publication Details

Journal
AEA Papers and Proceedings
Published
2025-05-01
DOI
https://doi.org/10.1257/pandp.20251061
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Heterogeneity in Effects of Poverty-Alleviating Interventions

Robert Garlick, John R. Walker, Kate Orkin
AEA Papers and Proceedings
Advanced Causal Inference Techniques
article

Heterogeneity in Effects of Poverty-Alleviating Interventions

Robert Garlick, John R. Walker, Kate Orkin
article en

Abstract

To what extent are poverty-alleviating interventions general tools? We revisit a 415-village cluster-randomized field experiment involving 8,300 women living in poverty in rural Kenya. We estimate the extent of heterogeneity in a cash transfer intervention, an aspirations-improving workshop, and their combination using median split regressions and causal forests. We find no evidence of heterogeneity with respect to a prespecified set of demographic, psychological, and economic welfare characteristics. We conclude that the poverty-alleviating interventions we consider are general tools that can assist a broad range of households experiencing poverty and economic shocks.

AEA Papers and ProceedingsVol. 115
Duke University (US), University of Oxford (GB)
Openalex Percentile: Top 88%
Advanced Causal Inference Techniques
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