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作者

来源

JOURNAL OF HOUSING ECONOMICS,Vol.35,P.26-36

语言

英文

关键字

Discrimination; Spatial steering; Rental housing market; Field experiment; Correspondence test; RACIAL-DISCRIMINATION; DETECTING DISCRIMINATION; RESIDENTIAL SEGREGATION; CONSUMER MARKETS; NEIGHBORHOOD; AUDIT; CITIES; RACE; PREFERENCES; LANDLORDS

作者单位

[Auspurg, Katrin] Ludwig Maximilians Univ Munchen, Dept Sociol, Konradstr 6, DE-80801 Munich, Germany. [Hinz, Thomas] Univ Konstanz, Dept Sociol, Box 40, DE-78457 Constance, Germany. [Schmid, Laura] Univ Augsburg, Alter Postweg 101, DE-86159 Augsburg, Germany. Auspurg, K (reprint author), Ludwig Maximilians Univ Munchen, Dept Sociol, Konradstr 6, DE-80801 Munich, Germany. E-Mail: Katrin.Auspurg@lmu.de; Thomas.Hinz@uni-konstanz.de; Laura.Schmid@qa.uni-augsburg.de

摘要

People's housing conditions and places of residence have serious impacts on individual well-being and social stratification. This article focuses on different forms of ethnic discrimination in the rental housing market. Several hypotheses on statistical discrimination, spatial steering, and discrimination by price were tested by a field experiment in Germany that was unique regarding both the amount of information available on rental units and on ethnic composition of neighborhoods. For 637 rental objects, two e-mail inquiries were sent out with applicants having German or Turkish names and varying occupations. Logistic random intercept regressions revealed a discrimination rate against Turkish applicants of 9 percentage points. Indicating a high occupational status in the application reduced this discrimination rate significantly, but private landlords tended to disregard status and discriminate by migration background only. Surprisingly, the discrimination against Turkish applicants was the strongest when the proportion of Turkish residents living in the neighborhood was highest. German applicants were particularly favored over Turks when making applications for reasonably priced objects. These results point to both core mechanisms driving discrimination (preference and information) being relevant, but in different market segments. (C) 2017 Published by Elsevier Inc.