, Volume 33, Issue 1-2, pp 37-54

Adjusting to natural disasters

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Abstract

People adjust to the risks presented by natural disasters in a number of ways; they can move out of harms way, they can self protect, or they can insure. This paper uses Hurricane Andrew, the largest U.S. natural disaster prior to Katrina, to evaluate how people and housing markets respond to a large disaster. Our analysis combines a unique ex post database on the storm’s damage along with information from the 1990 and 2000 Censuses in Dade County, Florida where the storm hit. The results suggest that the economic capacity of households to adjust explains most of the differences in demographic groups’ patterns of adjustment to the hurricane damage. Low income households respond primarily by moving into low-rent housing in areas that experienced heavy damage. Middle income households move away to avoid risk, and the wealthy, for whom insurance and self-protection are most affordable, appear to remain. This pattern of adjustment with respect to income is roughly mean neutral, so an analysis based on measures of central tendency such as median income would miss these important adjustments.

JEL Classification Q51 · Q54
W.P. Carey Professor of Economics, Arizona State University, and Resources for the Future, University Fellow; Assistant Professor, Williams College; Assistant Professor Virginia Tech; Affiliated Economist, CEnREP, North Carolina Sate University; Graduate Student, University of North Carolina at Chapel Hill, respectively. Smith’s research was partially supported by the United States Department of Homeland Security through the Center for Risk and Economic Analysis of Terrorism Events (CREATE), grant number EMW-2004-GR-0112. However, any opinion, findings, and conclusions or recommendations in this document are those of the author(s) and do not necessarily reflect views of the U.S. Department of Homeland Security. Thanks are due to H. Spencer Banzhaf, Kathleen Bell, David Card, Matt Kahn, Richard Ready, Kip Viscusi, and participants in Harvard’s Kennedy School and Texas A&M University’s Environmental Economics Workshops for very helpful comments on earlier summaries of this research. Thanks are also due Alex Boutaud, Susan Hinton, and Kenny Pickle for assistance in preparing the manuscript.