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Replication data for: Natural Hazards and Economic Losses: Why Correcting Sample Selection Matters

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication data for: Natural Hazards and Economic Losses: Why Correcting Sample Selection Matters
 
Identifier https://doi.org/10.7910/DVN/DMJCPG
 
Creator Song, Dahye
Choirat, Christine
 
Publisher Harvard Dataverse
 
Description Economic losses from natural disasters vary by countries, and it has been hypothesized that institutional, political, and other national conditions and policies all play a role in determining the severity of loss. Many empirical studies for understanding the determinants of disaster losses, however, suffer from endogeneity and selection bias, which can potentially make their results method-dependent. To demonstrate, we investigate the relationship between disaster propensity, wealth, and economic loss from a panel data collected by [Neumayer et al., 2014]. We first demonstrate that the original data is subject to endogeneity and selection bias, reconstruct the dataset, and apply Heckman correction. The bias-corrected estimated impact of disaster propensity changes direction from the original result by [Neumayer et al., 2014] — countries that experience more frequent disasters tend to suffer from greater economic damage, holding everything else equal. We suggest that disaster propensity could be an indicator of vulnerability, or a sign of insufficient prevention and mitigation measures. Although we cannot provide any definitive explanation for the phenomenon, our result shows that correcting selection bias matters when dealing with natural disasters data. For future work, a more sophisticated construction of the latent propensity variable and the application of quantile regression for endogenous selection models could broaden our understanding.
 
Subject Social Sciences
 
Contributor Song, Dahye