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Local housing price index analysis in wind-disaster-prone areas

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  • Bradley Ewing
  • Jamie Kruse
  • Yongsheng Wang

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Abstract

This study examines the effect of severe wind events on the mean and variance of housing price indices of six metropolitan statistical areas (MSA) that are vulnerable to hurricanes and/or tornadoes. The research focuses on three areas that experienced significant tornado activity (Fort Worth-Arlington, Nashville, and Oklahoma City) and three hurricane-prone areas (Corpus Christi, Miami, and Wilmington, NC). An econometric time series model that captures the housing market responses to severe windstorms is utilized. The model estimates changes in the local housing price index (HPI) as a function of several control variables as well as dichotomous variables that correspond to the tornadoes and hurricanes. As expected, the statistical findings indicate an immediate but short-lived decline in housing prices following a tornado or hurricane. Somewhat surprising is the result that the impact on the housing market is remarkably consistent whether the wind event was a hurricane or a tornado. Hurricanes and tornadoes are vastly different in terms of the point probabilities of a hit, the scope of the affected area and the lead time that supports last minute preparation to mitigate damage. It appears that the market response to destruction of real property does not distinguish between the types of wind event that produced the damage to the region. Results suggest that windstorms result in an immediate one-half to two percent reduction in total MSA housing value. This corresponds to a range of $34 million to $580 million in lost housing value. Estimates indicate some differences in how long market values continue to decline in the periods following the wind event; however, most of the decline occurs within four quarters after the windstorm. These differences can be attributed to the particular time series characteristics of the specific housing markets and their respective housing price indices. The market serves the purpose of integrating and normalizing the losses. In so doing the market provides a metric— a method for calibrating and comparing structural damage caused by different phenomenon. Copyright Springer Science+Business Media B.V. 2007

Suggested Citation

  • Bradley Ewing & Jamie Kruse & Yongsheng Wang, 2007. "Local housing price index analysis in wind-disaster-prone areas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 40(2), pages 463-483, February.
  • Handle: RePEc:spr:nathaz:v:40:y:2007:i:2:p:463-483
    DOI: 10.1007/s11069-006-9005-1
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    References listed on IDEAS

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    1. Kevin M. Simmons & Jamie Brown Kruse & Douglas A. Smith, 2002. "Valuing Mitigation: Real Estate Market Response to Hurricane Loss Reduction Measures," Southern Economic Journal, Southern Economic Association, vol. 68(3), pages 660-671, January.
    2. David M. Harrison & Greg T. Smersh & Arthur L. Schwartz, Jr, 2001. "Environmental Determinants of Housing Prices: The Impact of Flood Zone Status," Journal of Real Estate Research, American Real Estate Society, vol. 21(1/2), pages 3-20.
    3. Kevin M. Simmons & Jamie Brown Kruse, 2000. "Market Value of Mitigation and Perceived Risk: Empirical Results," Journal of Economic Insight (formerly the Journal of Economics (MVEA)), Missouri Valley Economic Association, vol. 26(1), pages 41-51.
    4. Fergus, James T, 1999. "Where, When, and by How Much Does Abnormal Weather Affect Housing Construction?," The Journal of Real Estate Finance and Economics, Springer, vol. 18(1), pages 63-87, January.
    5. James C. Murdoch & Harinder Singh & Mark Thayer, 1993. "The Impact of Natural Hazards on Housing Values: The Loma Prieta Earthquake," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 21(2), pages 167-184, June.
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    Citations

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    Cited by:

    1. Kevin Simmons & Daniel Sutter, 2007. "Tornado shelters and the manufactured home parks market," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 43(3), pages 365-378, December.
    2. Blackwell, Calvin & Sheldon, Susannah & Lansbury, David & Vaught, Dyanne, 2010. "Beach Re-nourishment and Property Value Growth: The Case of Folly Beach, South Carolina," The Review of Regional Studies, Southern Regional Science Association, vol. 40(3), pages 273-286.
    3. Yuepeng Cui & Daan Liang & Bradley T. Ewing & Ali Nejat, 2016. "Development, specification and validation of Hurricane Resiliency Index," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(3), pages 2149-2165, July.
    4. Bradley T. Ewing & Daan Liang & Yuepeng Cui, 2014. "A Time Series Approach to Examining Regional Economic Resiliency to Hurricanes," American Journal of Economics and Sociology, Wiley Blackwell, vol. 73(2), pages 369-391, April.
    5. Sutter Daniel & Ewing Bradley T., 2016. "State of Knowledge of Economic Value of Current and Improved Hurricane Forecasts," Journal of Business Valuation and Economic Loss Analysis, De Gruyter, vol. 11(1), pages 45-64, June.
    6. Cheung, Ron & Wetherell, Daniel & Whitaker, Stephan, 2018. "Induced earthquakes and housing markets: Evidence from Oklahoma," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 153-166.

    More about this item

    Keywords

    Housing prices; Tornado; Hurricane; Wind; Q540; R310; R210; C220;

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