Natural Disasters and Relief Assistance: Empirical Evidence on the Resilience of U.S. Counties Using Dynamic Propensity Score Matching

22 Pages Posted: 6 Jun 2018

See all articles by Daniele Bondonio

Daniele Bondonio

University of Piemonte Orientale

Robert T. Greenbaum

Ohio State University - John Glenn College of Public Affairs

Date Written: June 2018

Abstract

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.

Keywords: disaster recovery, economic development, natural disasters, propensity score matching, resilience

Suggested Citation

Bondonio, Daniele and Greenbaum, Robert T., Natural Disasters and Relief Assistance: Empirical Evidence on the Resilience of U.S. Counties Using Dynamic Propensity Score Matching (June 2018). Journal of Regional Science, Vol. 58, Issue 3, pp. 659-680, 2018, Available at SSRN: https://ssrn.com/abstract=3191603 or http://dx.doi.org/10.1111/jors.12379

Daniele Bondonio (Contact Author)

University of Piemonte Orientale

Robert T. Greenbaum

Ohio State University - John Glenn College of Public Affairs ( email )

United States

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