Staff Reports
Clustering in Natural Disaster Losses
Number 1135
November 2024

JEL classification: Q50, Q54

Authors: Jacob Kim-Sherman and Lee Seltzer

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.

Full Article
Author Disclosure Statement(s)
Jacob Kim-Sherman
Jacob Kim-Sherman declares that (s)he has no relevant or material financial interests that relate to the research described in this paper. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy, available at https://www.newyorkfed.org/research/staff_reports/index.html.

Lee Seltzer
Lee Seltzer declares that (s)he has no relevant or material financial interests that relate to the research described in this paper. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy, available at https://www.newyorkfed.org/research/staff_reports/index.html.
Suggested Citation:
Kim-Sherman, Jacob, and Lee Seltzer. 2024. “Clustering in Natural Disaster Losses.” Federal Reserve Bank of New York Staff Reports, no. 1135, November. https://doi.org/10.59576/sr.1135

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