This paper utilizes a novel dynamic propensity score matching approach for multiple cohorts of U.S. counties between 1989 and 1999 to examine local economy resilience to rare natural disasters. Affected counties are sorted based on disaster intensity and are carefully matched to similar counties that did not experience a disaster. A difference‐in‐difference estimator compares trends of affected counties’ postdisaster business establishments, employment, and payroll to counterfactual trends in the matched counties. All affected counties experienced short‐run drops in economic activity that was particularly noticeable in higher‐intensity disasters. In the longer run, less distressed counties returned to their estimated counterfactual trends, but counties with lower predisaster socioeconomic conditions still lagged in growth, particularly in cases of lower‐intensity disasters. Policymakers can use this information to better prepare responses to future disasters.
Bondonio, Daniele and Robert T. Greenbaum, 2018 “Natural Disasters and Relief Assistance: Empirical Evidence on the Resilience of U.S. Counties using Dynamic Propensity Score Matching,” Journal of Regional Science, 58(3): 659-680.