Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/309140 
Year of Publication: 
2025
Series/Report no.: 
Staff Reports No. 1135
Version Description: 
Revised January 2025
Publisher: 
Federal Reserve Bank of New York, New York, NY
Abstract: 
Empirical research in climate economics often relies on panel regressions of different outcomes on disaster damages. Interpreting these regressions requires an assumption that error terms are uncorrelated across counties and time, which climate science research suggests is unlikely to hold. We introduce a methodology to identify spatial and temporal clusters in natural disaster damages datasets, and show that accounting for clustering affects observed economic effects of disasters. Specifically, counties tend to experience 0.45% more disaster damage for every 1% increase in damage across other intra-cluster counties. Moreover, accounting for clustering makes some hazard types, such as droughts, appear more damaging.
Subjects: 
natural disasters
clustering
JEL: 
Q50
Q54
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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