Clustering in natural disaster losses

In contrast with findings in climate science, economists often treat losses from natural disasters as statistically independent of one another. To better incorporate scientific insights into economic research, we introduce a methodology to identify spatial and temporal clusters in datasets on losses from natural disasters. We find that expected damage increases non-linearly with relative cluster size. Additionally, county-level damage is correlated with the damage experienced by other counties in the same cluster. Our findings suggest that accounting for clustering allows for a more complete understanding of the economic consequences of natural disasters.