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Homeowner Preferences after September 11th, a Microdata Approach

Author

Listed:
  • Adam Nowak

    (West Virginia University, Department of Economics)

  • Juan Sayago-Gomez

    (West Virginia University, Department of Economics)

Abstract
The existence of homeowner preferences - specifically homeowners' preferences for neighbors - is fundamental to economic models of sorting. This paper investigates whether or not the terrorist attacks of September 11, 2001 (9/11) impacted on local preferences for Arab neighbors. We test for changes in preferences using a differences-in-differences framework in a hedonic pricing model. Relative to sales before 9/11, we find properties within 0.1 miles of an Arab homeowner sold at a 1.5% discount in the 180 days after 9/11. The results are robust to a number of specifications including time horizon, event date, distance, alternative ethnic groups, and the presence of nearby mosques. Previous research has shown price effects at neighborhood levels but has not identified effects at the micro or individual property level, and for good reason: most transaction level data sets do not include ethnic identifiers. Applying methods from the machine learning and biostatistics literature, we develop a binomial classifier using a supervised learning algorithm and identify Arab homeowners based on the name of the buyer. We train the binomial classifier using names from Summer Olympic Rosters for 221 countries during the years 1948-2012. We demonstrate the exibility of our methodology and perform an interesting counterfactual by identifying Hispanic and Asian homeowners in the data; unlike the statistically significant results for Arab homeowners, we find no meaningful results for Hispanic and Asian homeowners following 9/11.

Suggested Citation

  • Adam Nowak & Juan Sayago-Gomez, 2017. "Homeowner Preferences after September 11th, a Microdata Approach," Working Papers 17-03, Department of Economics, West Virginia University.
    • Handle: RePEc:wvu:wpaper:17-03
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    File URL: http://busecon.wvu.edu/phd_economics/pdf/17-03.pdf
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    Cited by:

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    2. Lepage, Louis-Pierre, 2023. "Discrimination and sorting in the real estate market: Evidence from terrorist attacks and mosques," European Economic Review, Elsevier, vol. 153(C).
    3. Kathleen Grace & Joshua C. Hall, 2019. "The Value of Residential Community Associations: Evidence from South Carolina," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 121-129, February.
    4. David Rey-Blanco & Pelayo Arbués & Fernando A. López & Antonio Páez, 2024. "Using machine learning to identify spatial market segments. A reproducible study of major Spanish markets," Environment and Planning B, , vol. 51(1), pages 89-108, January.
    5. Jamie Bologna Pavlik & Yang Zhou, 2023. "Are historic districts a backdoor for segregation? Yes and no," Contemporary Economic Policy, Western Economic Association International, vol. 41(3), pages 415-434, July.
    6. Elster, Yael & Zussman, Noam, 2024. "Minorities and property values: Evidence from residential buildings in Israel," Journal of Urban Economics, Elsevier, vol. 141(C).

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    More about this item

    Keywords

    house prices; ethnicity; homeowner preferences; terrorism; September 11th;
    All these keywords.

    JEL classification:

    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination

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