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Estimating the Wage Premia of Refugee Immigrants: Lessons from Sweden
Boston Coll, USA;Ctr Excellence Sci & Innovat Studies CESIS, Sweden.
KTH Royal instute of technology, Sweden.
Linnaeus University, Faculty of Technology, Department of Forestry and Wood Technology. DIW Berlin, Germany.ORCID iD: 0000-0001-5776-9396
Econ & Human Resources Innovat UNU MERIT, Netherlands;Maastricht Univ, Netherlands;CEPR, USA;Univ Bonn, Germany;Global Lab Org GLO, Netherlands.
2024 (English)In: Industrial & labor relations review, ISSN 0019-7939, E-ISSN 2162-271X, Vol. 77, no 4, p. 562-597Article in journal (Refereed) Published
Abstract [en]

This article examines the wage earnings of refugee immigrants in Sweden. Using administrative employer-employee data from 1990 onward, approximately 100,000 refugee immigrants who arrived between 1980 and 1996 and were granted asylum are compared to a matched sample of native-born workers. Employing recentered influence function (RIF) quantile regressions to wage earnings for the period 2011-2015, the occupational-task-based Oaxaca-Blinder decomposition approach shows that refugees perform better than natives at the median wage, controlling for individual and firm characteristics. This overperformance is attributable to female refugee immigrants. Given their characteristics, refugee immigrant females perform better than native females across all occupational tasks studied, including non-routine cognitive tasks. A notable similarity of the wage premium exists among various refugee groups, suggesting that cultural differences and the length of time spent in the host country do not have a major impact.

Place, publisher, year, edition, pages
Sage Publications, 2024. Vol. 77, no 4, p. 562-597
Keywords [en]
refugees, wage earnings gap, occupations, gender, employer-employee data, job-tasks, recentered influence function (RIF) quantile regressions
National Category
Economics
Research subject
Economy, Economics
Identifiers
URN: urn:nbn:se:lnu:diva-131730DOI: 10.1177/00197939241261640ISI: 001250710500001Scopus ID: 2-s2.0-85197642461OAI: oai:DiVA.org:lnu-131730DiVA, id: diva2:1889042
Available from: 2024-08-14 Created: 2024-08-14 Last updated: 2024-09-05Bibliographically approved

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Stephan, Andreas

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