Experimental Evidence of Discrimination in the Labour Market: Intersections between Ethnicity, Gender, and Socio-Economic Status
Abstract
This article presents evidence of ethnic discrimination in the recruitment process from a field experiment conducted in the Danish labour market. In a correspondence experiment, fictitious job applications were randomly assigned either a Danish or Middle Eastern-sounding name and sent to real job openings. In addition to providing evidence on the extent of ethnic discrimination in the Danish labour market, the study offers two novel contributions to the literature more generally. First, because a majority of European correspondence experiments have relied solely on applications with male aliases, there is limited evidence on the way gender and ethnicity interact across different occupations. By randomly assigning gender and ethnicity, this study suggests that ethnic discrimination is strongly moderated by gender: minority males are consistently subject to a much larger degree of discrimination than minority females across different types of occupations. Second, this study addresses a key critique of previous correspondence experiments by examining the potential confounding effect of socio-economic status related to the names used to represent distinct ethnic groups. The results support the notion that differences in callbacks are caused exclusively by the ethnic traits.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Dahl & Krog (2018) found significantly more discrimination against men with Arabic-sounding names contrasted with women in Denmark.
“In Denmark, Dahl & Krog (2018) find significantly more discrimination against men with Arabic-sounding names contrasted with women.”
From Comparative Perspectives on Racial Discrimination in Hiring: The Rise of Field Experiments (2021) · cites this paper as Dahl & Krog (2018)
Cites
Ethnic Discrimination in Germany’s Labour Market: A Field Experiment
Kaas, L., & Manger, C. (2012) · German Economic Review · doi:10.1111/j.1468-0475.2011.00538.x · Cited by 509 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Comparative Perspectives on Racial Discrimination in Hiring: The Rise of Field Experiments
Quillian, L., & Midtbøen, A. H. (2021) · Annual Review of Sociology · doi:10.1146/annurev-soc-090420-035144 · Cited by 180 · see citing works
Who can ride along? Discrimination in a German carpooling market
Carol, S., Eich, D., Keller, M., Steiner, F., & Storz, K. (2019) · Population, Space and Place · doi:10.1002/psp.2249 · Cited by 28 · see citing works
- Authors
- Dahl, M., & Krog, N.
- Affiliations
- University of Copenhagen (DK)
- Corresponding author
- Dahl, Malte
- ORCID
- Dahl, Malte
- Venue
- European Sociological Review
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-06-29
- Volume
- 34
- Issue
- 4
- Pages
- 402-417
- ISSN
- 0266-7215 (ISSN-L)
- 1468-2672
- OpenAlex
- W2887659879
- Cited by
- 79
- References
- 1
- Citations by year
- 2026: 11 · 2025: 12 · 2024: 12 · 2023: 17 · 2022: 6 · 2021: 9 · 2020: 6 · 2019: 3 · 2018: 2 · 2015: 1
- FWCI
- 10.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Sociological Review (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Names, Identity, and Discrimination Research
- Social Sciences › Gender Studies › Labour Market and Migration
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Keywords
- ethnic discrimination, employment discrimination, gender discrimination, socioeconomic status, correspondence experiment, job applications, callbacks, intersectionality, minority males, Danish labour market
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review