Résumé

This paper studies the question of how to target aid after a natural disaster. Disaster aid programs often use property damage as a criterion for eligibility. A household’s ability to insure against shocks is harder to observe, but it may be more important in determining how the disaster affects welfare. I develop a model of household demand for reconstruction aid, incorporating both the exposure to a shock and the ability to borrow for consumption smoothing. I calibrate the model using household survey data following the 2015 earthquake in Nepal, and I use a spatial discontinuity in the distribution of reconstruction aid to test the model’s assumptions. Aid increases consumption and housing investment, but decreases remittances, consistent with a model of incomplete insurance. I use the calibrated model to estimate the benefits of counterfactual aid allocations. Conditioning aid on household property damage barely outperforms allocating aid at random. The property damage criterion excludes many liquidity-constrained households that have high demand for aid, and it includes wealthy, well-insured households that have low demand. An untargeted approach that divides the aid budget equally between all households in the affected areas yields substantially larger welfare gains. Spending resources to assess physical damages for targeting purposes is thus unlikely to be cost effective.  

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