Shelter from the Storm: A Simulation Framework for Vulnerability under Climate Shocks

Gustavo Canavire Bacarreza (), Alejandro Puerta-Cuartas (), Carlos Rodriguez Castelan () and Carolina Velez-Ospina ()
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Gustavo Canavire Bacarreza: World Bank
Alejandro Puerta-Cuartas: Banco de España
Carlos Rodriguez Castelan: World Bank
Carolina Velez-Ospina: World Bank

No 18893, IZA Discussion Papers from IZA Network @ LISER

Abstract: This paper proposes a nonparametric simulation framework to estimate poverty vulnerability under climate shocks. We formalize vulnerability estimation as an out-of-sample prediction problem and show that flexible, regularized machine learning methods for estimating the conditional mean of welfare offer a powerful alternative to conventional linear models. The framework simulates future welfare distributions using historical realizations of climate shocks and household characteristics, enabling the estimation of vulnerability measures and related functions without imposing restrictive parametric assumptions. To interpret the model and quantify heterogeneous impacts, we employ SHapley Additive exPlanations, which decompose predicted vulnerability into contributions from climate shocks and household characteristics. An application to Ecuador reveals a strong geographic concentration of vulnerability and shows that climate shocks act as localized triggers that push marginal households, particularly low-educated informal rural workers into poverty.

Keywords: Poverty Vulnerability; Climate Shocks; Machine Learning. (search for similar items in EconPapers)
JEL-codes: C14 C15 I32 I38 (search for similar items in EconPapers)
Date: 2026-09
New Economics Papers: this item is included in nep-res
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Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp18893

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