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

Tatjana Miljkovic , Dragan Miljkovic

International Journal of Disaster Risk Science ›› 2014, Vol. 5 ›› Issue (4) : 265 -273.

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International Journal of Disaster Risk Science ›› 2014, Vol. 5 ›› Issue (4) : 265 -273. DOI: 10.1007/s13753-014-0030-5
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Modeling Impact of Hurricane Damages on Income Distribution in the Coastal U.S.

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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.

Keywords

Hurricane damages / Income distribution / Disaster insurance / United States

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Tatjana Miljkovic, Dragan Miljkovic. Modeling Impact of Hurricane Damages on Income Distribution in the Coastal U.S.. International Journal of Disaster Risk Science, 2014, 5(4): 265-273 DOI:10.1007/s13753-014-0030-5

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References

[1]

ABC News. 2005. Poorest hit hardest by Hurricane Katrina, 30 August 2005. http://abcnews.go.com/WNT/HurricaneKatrina/story?id=1081329. Accesses 30 Dec 2012.

[2]

Annan, K. 1999. An increasing vulnerability to natural disasters. New York Times, 10 September 1999. http://www.nytimes.com/1999/09/10/opinion/10iht-edannan.2.t.html. Accessed 18 Sept 2014.

[3]

Ansolabehere S, Snyder JM Jr Party control of state government and the distribution of public expenditures. The Scandinavian Journal of Economics, 2006, 108(4): 547-569 10.1111/j.1467-9442.2006.00470.x

[4]

Baltagi BH. Econometric analysis of panel data, 1999, New York: Wiley

[5]

Becker GS. A theory of competition among pressure groups for political influence. The Quarterly Journal of Economics, 1983, 98(3): 371-400 10.2307/1886017

[6]

Black HC. Black’s law dictionary, 1990 6 Saint Paul, MN: West Publishing

[7]

Brendler M, Jones CA. Income distribution determinants within adjacent states: The case of louisiana and texas. Southwestern Economic Review, 1994, 21(1): 71-79.

[8]

Carroll CD. Buffer-stock saving and the life cycle/permanent income hypothesis. The Quarterly Journal of Economics, 1997, 112(1): 1-55 10.1162/003355397555109

[9]

Carroll CD, Summers LH. Bernheim BD, Shoven JB. Consumption growth parallels income growth: Some new evidence. National saving and economic performance, 1991, Chicago: The University of Chicago Press 305-343.

[10]

Changnon SA. The great flood of 1993: Causes, impacts and responses, 1996, Boulder, CO: Westview Press

[11]

Collins, D.J., and S.P. Lowe. 2001. A macro validation dataset for U.S. hurricane model. Casualty Actuarial Society Forum, Casualty Actuarial Society, Arlington, VA. http://www.casact.org/pubs/forum/01wforum/01wf217.pdf. Accessed 18 Sept 2014.

[12]

CRS (Congressional Research Service). 2008. CRS report for congress. Emergency supplemental appropriations legislation for disaster assistance: Summary data (Updated 31 October 2008). http://assets.opencrs.com/rpts/RL33226_20081031.pdf. Accessed 31 Dec 2013.

[13]

Fields GS. Accounting for income inequality and its change: a new method, with application to the distribution of earnings in the United States. Research in Labor Economics, 2003, 22: 1-38 10.1016/S0147-9121(03)22001-X

[14]

Frank, M.W. 2008. A new state-level panel of income inequality measures over the period 1916–2005. SHSU (Sam Houston State University) Economics and International Business Working Paper, No. SHSU_ECO_WP08-02.

[15]

Gronn A. Capacity constraints and cycles in property–casualty insurance markets. The Rand Journal of Economics, 1994, 25(1): 110-127 10.2307/2555856

[16]

Guimaraes, P., P.L. Hefner, and D.P. Woodward. 1992. Wealth and income effects of natural disasters: An econometric analysis of Hurricane Hugo. Working Paper: Division of Research, College of Business Administration, University of South Carolina.

[17]

Hall RE. Stochastic implications of the life cycle-permanent income hypothesis: Theory and evidence. Journal of Political Economy, 1978, 86(6): 971-987 10.1086/260724

[18]

Kahn EM. The death toll from natural disasters: The role of income, geography, and institutions. The Review of Economics and Statistics, 2005, 87(2): 271-284 10.1162/0034653053970339

[19]

Kellenberg DK, Mobarak AM. Does rising income increase or decrease damage risk from natural disasters?. Journal of Urban Economics, 2008, 63(3): 788-802 10.1016/j.jue.2007.05.003

[20]

Logan, J.R. 2006. The impact of Katrina: Race and class in storm-damaged neighborhoods. S4, Special Structures in the Social Science, Hurricane Katrina Project. Providence, RI: Brown University. http://www.s4.brown.edu/Katrina/report.pdf. Accessed 27 Dec 2012.

[21]

Madden JF. Changes in income inequality within U.S. metropolitan areas, 2000, Kalamazoo: MI: W.E. Upjohn Institute for Employment Research

[22]

Masozera M, Bailey M, Kerchner C. Distribution of impacts of natural disasters across income groups: A case study of New Orleans. Ecological Economics, 2007, 63(2–3): 299-306 10.1016/j.ecolecon.2006.06.013

[23]

McDonald JB, Jensen BC. An analysis of some properties of alternative measures of income inequality based on the gamma distribution function. Journal of the American Statistical Association, 1979, 74(368): 856-860 10.1080/01621459.1979.10481042

[24]

Milanovic B. A simple way to calculate the Gini coefficient, and some implications. Economics Letters, 1997, 56(1): 45-49 10.1016/S0165-1765(97)00101-8

[25]

Moore, A. 2012. Seven years after hurricane Katrina: Who owes whom? http://www.huffingtonpost.com/amanda-moore/katrina-anniversary_b_1841165.html. Accessed 11 Jan 2014.

[26]

Pielke RA Jr Landsea CW. La Niña, El Niño, and Atlantic hurricane damages in the United States. Bulletin of the American Meteorological Society, 1999, 80(10): 2027-2033 10.1175/1520-0477(1999)080<2027:LNAENO>2.0.CO;2

[27]

Pielke RA Jr Gratz J, Landsea CW, Collins D, Saunders MA, Musulin R. Normalized hurricane damage in the United States: 1900–2005. Natural Hazards Review, 2008, 9(1): 29-42 10.1061/(ASCE)1527-6988(2008)9:1(29)

[28]

Pindyck RS, Rubinfeld DL. Econometric models and economic forecasts, 1998 4 Boston, MA: Irwin/McGraw-Hill

[29]

Ravallion M, Chen S. What can new survey data tell us about recent changes in distribution and poverty?. The World Bank Economic Review, 1997, 11(2): 357-382 10.1093/wber/11.2.357

[30]

Shaughnessy TM, White ML, Brendler MD. The income distribution effect of natural disasters: An analysis of Hurricane Katrina. Journal of Regional Analysis and Policy, 2010, 40(1): 84-95.

[31]

Toya H, Skidmore M. Economic development and the impacts of natural disasters. Economics Letters, 2007, 94(1): 20-25 10.1016/j.econlet.2006.06.020

[32]

United States Bureau of Economic Analysis. 2013. Regional data: GDP & personal income. http://www.bea.gov/iTable/iTable.cfm?ReqID=70&step=1#reqid=70&step=7&isuri=1&7001=1200&7002=1&7003=200&7090=70&7005=1&7006=01000&7093=levels&7004=sic. Last accessed 27 Dec 2013.

[33]

United States Census Bureau. 2013. Population estimates at state level. http://www.census.gov/popest/data/historical/index.html. Accessed 19 Nov 2013.

[34]

United States House of Representatives. 2013. http://www.house.gov/. Accessed 19 Nov 2013.

[35]

United States Senate. 2013. http://www.senate.gov/. Accessed 19 Nov 2013.

[36]

United States Congress. 2014. H.R. 3370-Homeowner flood insurance affordability act of 2014. Public Law No. 113-89. https://beta.congress.gov/bill/113th-congress/house-bill/3370. Accessed 18 Sept 2014.

[37]

Vellinga P, Mills E. McCarthy J, Caniziani O, Leary N, Dokken D, White K. Insurance and other financial services. Climate change 2001: Impacts, adaptation and vulnerability. Working Group II, Intergovernmental Panel on Climate Change, 2001, Cambridge, U.K: Cambridge University Press 451-486.

[38]

West CT, Lenze DG. Modeling the regional impact of natural disaster and recovery: A general framework and an application to Hurricane Andrew. International Regional Science Review, 1994, 17(2): 121-150 10.1177/016001769401700201

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