Ethnic and gender discrimination in the rental housing market: Evidence from a meta-analysis of correspondence tests, 2006–2017

Citation data:

Journal of Housing Economics, ISSN: 1051-1377, Vol: 41, Page: 251-273

Publication Year:
2018
Captures 1
Readers 1
Social Media 28
Tweets 28
DOI:
10.1016/j.jhe.2018.07.003
Author(s):
Alexandre Flage
Publisher(s):
Elsevier BV
Tags:
Economics, Econometrics and Finance
Most Recent Tweet View All Tweets
article description
We present a broad review of all studies having tested for discrimination against minority ethnic groups in the rental housing market by the correspondence testing method. We perform a meta-analysis of correspondence tests from 25 separate studies conducted in OECD countries between 2006 and 2017, containing more than 300 estimates of effects and representing a total of more than 110,000 e-mails sent to private landlords or real-estate agents. In addition to presenting overall results of recent studies, we focus on subgroups of specific correspondence tests in order to highlight the differences in ethnicity, gender, type of landlords, procedure, continent, and type of information provided in applications. We provide evidence that both gender and ethnic discrimination occur in the rental housing market in OECD countries, such that applicants with minority-sounding names and male names are discriminated against (especially Arab/Muslim applicants). Thus, ethnic majority women are the most favored in this market in OECD countries while minority men are the most disadvantaged. Moreover, we show the existence of interactions between ethnic and gender discrimination: gender discrimination is greater for minority-sounding names than for majority-sounding names. Finally, it seems that real-estate agents discriminate significantly less against minority applicants than private landlords do. This would seem to be at least in part because private landlords display significant statistical discrimination while real-estate agents do not. These results are robust to the estimation methods used (random effects, fixed-effects, and unrestricted weighted least squares methods).