Estimating the wage premia of refugee immigrants: Lessons from Sweden

Christopher F. Baum, Hans Lööf, Andreas Stephan, Klaus Zimmermann

Research output: Working paper / PreprintWorking paper

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Abstract

This paper examines the wage earnings of fully-employed previous refugee immigrants in Sweden. Using administrative employer-employee data from 1990 onwards, about 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 re-centered 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 due to female refugee immigrants, who have—relative to their endowment—higher wages than comparable native-born female peers up to the 8th decile of the wage distribution. Given their endowments, refugee immigrant females perform better than native females across all occupational tasks studied, including non-routine cognitive tasks. A remarkable similarity exists in the relative wage distributions among various refugee groups, suggesting that cultural differences and the length of time spent in the host country do not significantly affect their labor market performance.
Original languageEnglish
PublisherUNU-MERIT
Publication statusPublished - 26 Feb 2024
Externally publishedYes

Publication series

SeriesUNU-MERIT Working Papers
Number004
ISSN1871-9872

JEL classifications

  • o15 - "Economic Development: Human Resources; Human Development; Income Distribution; Migration"
  • j60 - Mobility, Unemployment, and Vacancies: General
  • j24 - "Human Capital; Skills; Occupational Choice; Labor Productivity"
  • f22 - International Migration
  • c23 - "Single Equation Models; Single Variables: Models with Panel Data; Longitudinal Data; Spatial Time Series"

Keywords

  • Blinder–Oaxaca decomposition
  • correlated random effects model
  • employer-employee data
  • occupational sorting
  • wage earnings gap
  • refugees

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