Riders on the Storm: Hurricane Risk and Coastal Insurance and Mitigation Decisions

Dan Petrolia,Scott Shonkwiler,Craig E. Landry,Harrison Laird

doi:10.15351/2373-8456.1128

Abstract

This paper utilizes cross-sectional, household-level, survey data combined with data on subjective risk perceptions and experimentally derived risk preferences to analyze the decision to insure against hurricane losses. Our sample encompasses 670 individuals in five states of the United States Gulf Coast Region (Texas, Louisiana, Mississippi, Alabama, and Florida). This study represents one of the few papers to examine wind insurance empirically and the only study to examine flood insurance, wind insurance, and mitigation behavior contemporaneously. Because these decisions are closely related, we employ a mixed-process regression, which allows for correlated error terms across a random-effects bivariate probit model (flood/wind insurance) and a Poisson Log-Normal count model (mitigation). Results indicate positive and statistically significant correlations between the error terms of the insurance and mitigation models but no significant correlation between the error terms of the two insurance models, conditioned on the covariates. We find evidence that risk perceptions and other household factors have some influence on storm risk management, but the strongest effects tend to be related to mandatory insurance requirements associated with location in high-hazard areas.

Highlights

Since the late 20th century, hurricanes and the resulting floods have been the costliest of all natural disasters in the United States both in terms of lives lost and property damaged
Major issues which have caused many private insurers to withdraw from the market include: certainty of loss in flood prone areas, adverse selection, moral hazard stemming from government disaster aid, and high premiums resulting in low uptake rates (Anderson, 1974; Petrolia, Landry, & Coble, 2013)
Positive correlation between the error terms of the flood insurance and mitigation equations (ρ f,m = 0.2173) as well as the wind insurance and mitigation equations

Summary

Introduction

Since the late 20th century, hurricanes and the resulting floods have been the costliest of all natural disasters in the United States both in terms of lives lost and property damaged. Increased precipitation may result from a more erratic climate, and rising sea levels will bring storm surge further inland, increasing the probability and negative consequences of major flooding incidents in some coastal areas. Exacerbating this problem are significant increases in population and housing investment in coastal areas of the United States. Spatial correlation of losses presents an especially difficult hurdle for private insurers because losses are not statistically independent This leads to an intertemporal smoothing problem in which insurance companies incur massive losses some years and zero losses in others (Michel-Kerjan, 2010; Kousky 2011). Though the program has been amended several times since the passage of the initial law, the overall structure and responsibilities of the respective stakeholders remains largely the same

Results

Discussion

Conclusion