Predicting household resilience with machine learning: preliminary cross-country tests

Alessandra Garbero and Marco Letta

Empirical Economics, 2022, vol. 63, issue 4, No 14, 2057-2070

Abstract: Abstract Using a unique cross-country sample from 10 impact evaluations of development projects, we test the out-of-sample performance of machine learning algorithms in predicting non-resilient households, where resilience is a subjective metrics defined as the perceived ability to recover from shocks. We report preliminary evidence of the potential of these data-driven techniques to identify the main predictors of household resilience and inform the targeting of resilience-oriented policy interventions.

Keywords: Resilience; Machine learning; Classification; Targeting; Predictive analytics (search for similar items in EconPapers)
JEL-codes: C52 O12 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00181-022-02199-4

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