Quantifying Racial Prejudices with Housing Transaction Data

Tin Cheuk Leung (), Xiaojin Sun () and Kwok Ping Tsang ()
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Tin Cheuk Leung: Wake Forest University, Economics Department, Postal: 1834 Wake Forest Rd., Winston-Salem, NC, 27109, https://sites.google.com/site/tincheukleung/
Xiaojin Sun: Oklahoma State University
Kwok Ping Tsang: Virginia Tech

No 117, Working Papers from Wake Forest University, Economics Department

Abstract: This paper aims to quantify racial prejudices using transaction-level housing market data. We pin down the impact of a marginal change of racial composition in a narrowly-defined neighborhood on the price appreciation between repeated sales of a house, and we find that an additional nonwhite household within a radius of 0.2 miles reduces the price appreciation by 1.27 percentage points. The effects are weaker in neighborhoods with a thicker housing market and a higher income level, suggesting that the role of racial prejudices is limited by market forces. The effects are also associated with voting behaviors and public anti-racism statements made on social media, indicating that they are likely to be driven by taste-based racial preferences. While we also find evidence of racial price discrimination effects as in the literature, these effects tend to be a form of statistical discrimination driven by other factors that correlate with race.

Keywords: Housing market; repeated sales; racial prejudices; machine learning (search for similar items in EconPapers)
JEL-codes: H00 J15 R23 R30 (search for similar items in EconPapers)
Pages: 55 pages
Date: 2024-10-17
New Economics Papers: this item is included in nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:ris:wfuewp:0117

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