Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/213856 
Year of Publication: 
2020
Citation: 
[Journal:] Research in Social Stratification and Mobility [ISSN:] 0276-5624 [Volume:] forthcoming [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2020
Publisher: 
Elsevier, Amsterdam
Abstract: 
This paper explores a possible sampling bias in field experiments through a unique combination of a large-scale field experiment on ethnic discrimination in the German rental housing market (N = 2,992 tested apartments) and data on the internet housing market where the apartments were sampled from (observation of the whole platform for about one year). Up to now, most field experiments sampled on the level of suppliers (not apartments) and selected the tested suppliers within a short field period (point sampling). This probably led to an over-representation of small suppliers and apartments that had already been advertised for a long time, resulting in an under-representation of large suppliers and new vacancies. We analyze how both issues affect the measurement of ethnic discrimination and its underlying mechanisms. With our case study on the German housing market, we first observed the expected sampling bias: There was a strong over-sampling of small suppliers and apartments already offered for a long time. Second, this bias was found to have only little impact on the descriptive result of substantial discrimination against Turkish applicants. There was only a slight tendency that discrimination was higher for small suppliers and offers advertised for a relatively short time (i.e. new vacancies). Overall, we conclude that evidence on ethnic discrimination and its underlying risk factors is remarkably robust to the used sampling technique. Although there were no indications of a severe bias, our market data illustrate opportunities to test the effects of market conditions that often remained unnoticed.
Subjects: 
Field experiment
Ethnic discrimination
Housing market
External validity
Sampling bias
Length bias
Market conditions
JEL: 
C93
C83
J15
R39
Published Version’s DOI: 
Creative Commons License: 
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Document Type: 
Article
Document Version: 
Accepted Manuscript (Postprint)
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