Modeling Impact of Hurricane Damages on Income Distribution in the Coastal U.S.

Abstract

This article examines the impact of catastrophic hurricane events on income distribution in hurricane states in the United States. Media claims have been made and the perception created that the most damaging impact of hurricanes is on the lowest income population in the affected states. If these claims are true, they may have serious implications for the insurance industry and government policy makers. We develop a panel data, fixed effects econometric model that includes hurricane-impacted states as cross-sections using annual data for a period of almost 100 years. The Gini coefficient is used as a measure of income inequality, and is a function of normalized hurricane economic damages, gross domestic product (GDP), a set of socioeconomic variables that serves as a control, time trend, and cross-sectional dummy variables. Findings indicate that for every 100 billion US dollars in hurricane economic damages there is an increase in income inequality by 5.4 % as measured by Gini coefficient. Political, sociodemographic, and economic variables are also significant. These include such variables as the political party controlling the U.S. Senate, the proportion of nonwhite population by state, and GDP. Time trend is a positive and significant variable, suggesting an increase in income inequality over time. There are significant differences among the states included in the study. Our results demonstrate that different segments of the population are differently impacted by hurricanes and suggest how that differential impact could be considered in future government policies and business decisions, particularly those made by the insurance industry.