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Storm Surges, Informational Shocks, and the Price of Urban Real Estate:An Application to the Case of Hurricane Sandy

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  • Jason Barr
  • Jeffrey P. Cohen
  • Eon Kim

Abstract

The impacts of a major hurricane on commercial and residential real estate can be devastating. Recent events in Houston (with Hurricane Harvey), Florida (with Hurricane Irma), and New York City (with Hurricane Sandy) are examples of how flooding damage can unexpectedly extend beyond the FEMA flood zones. Such surprises or shocks can provide property owners—including those that are not flooded—with new information about future flood risks, based on the difference of the property distance from the flood zone and the distance to the actual locations of flooding. We apply a new estimation strategy to quantify the effects of these shocks on property values, using information on repeat property sales to estimate a separate shock effect for each dry property. We demonstrate our approach with an application to non-flooded properties in New York City for Hurricane Sandy. We find that, in general, houses, apartments and commercial properties show the most price volatility within the older, denser urban core, mostly in those neighborhoods that appear to be gentrifying.

Suggested Citation

  • Jason Barr & Jeffrey P. Cohen & Eon Kim, 2017. "Storm Surges, Informational Shocks, and the Price of Urban Real Estate:An Application to the Case of Hurricane Sandy," Working Papers Rutgers University, Newark 2017-002, Department of Economics, Rutgers University, Newark.
  • Handle: RePEc:run:wpaper:2017-002
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    File URL: https://www.ncas.rutgers.edu/sandyhurricanejbarr
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    Cited by:

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    2. Meltzer, Rachel & Ellen, Ingrid Gould & Li, Xiaodi, 2021. "Localized commercial effects from natural disasters: The case of Hurricane Sandy and New York City," Regional Science and Urban Economics, Elsevier, vol. 86(C).
    3. Jeffrey P. Cohen & Felix L. Friedt & Jackson P. Lautier, 2022. "The impact of the Coronavirus pandemic on New York City real estate: First evidence," Journal of Regional Science, Wiley Blackwell, vol. 62(3), pages 858-888, June.
    4. Liang, Cong & Huang, Yaoxuan & Yip, Tsz Leung & Li, Victor Jing, 2022. "Does rail transit development gentrify neighborhoods? Evidence from Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 354-372.
    5. Di Yang & Anni Yang & Han Qiu & Yao Zhou & Hannah Herrero & Chiung-Shiuan Fu & Qiang Yu & Jingyin Tang, 2019. "A Citizen-Contributed GIS Approach for Evaluating the Impacts of Land Use on Hurricane-Harvey-Induced Flooding in Houston Area," Land, MDPI, vol. 8(2), pages 1-19, January.
    6. Jose J. Canals-Cerda & Raluca Roman, 2021. "Climate Change and Consumer Finance: A Very Brief Literature Review," Consumer Finance Institute discussion papers 21-04, Federal Reserve Bank of Philadelphia.

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    More about this item

    Keywords

    Hurricane Sandy; Storm Surges; New York City; Locally Weighted Regressions; Real Estate Prices;
    All these keywords.

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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