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PublicationWorking paper

Ratio Working Paper No. 335 International Trade and Labor Market Integration of Immigrants

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Abstract

We examine if international trade improves labor market integration of immigrants in Sweden. Immigrants participate substantially less than natives in the labor market. However, trading with a foreign country is expected to increase the demand for immigrants from that country. By hiring immigrants, a firm may access foreign knowledge and networks needed to overcome information frictions in trade. Using granular longitudinal matched employer–employee data and an instrumental variable approach, we estimate the causal effects of a firm’s bilateral trade on employment and wages of immigrants from that country. We find a positive, yet heterogeneous, effect of trade on immigrant employment but no effect on immigrant wages.

Lodefalk, M., Sjöholm, F. & Tang, A. (2020). International Trade and Labor Market Integration of Immigrants. Ratio Working Paper No. 335. Stockholm: Ratio.

Details

Author
Lodefalk, M., Sjöholm, F. & Tang, A.
Publication year
2020
Published in

Ratio Working Paper

Related

  • Associate Professor

    Magnus Lodefalk

    magnus.lodefalk@oru.se

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Article (with peer review)

Artificial Intelligence for Public Use

Lodefalk, M.; Engberg, E.; Lidskog, R.; Skargren, F.; Tang, A.
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Publication year

2026

Published in

Digital Society

Abstract

The public sector faces rising expectations, demographic change and persistent efficiency challenges. This article examines both the potential and limitations of AI in public services. Using an interdisciplinary conceptual framework, it analyses organisational, regulatory, technical and ethical barriers. It also simulates AI’s possible long-term effects on labour demand and productivity in Sweden using administrative data and occupational AI-exposure measures. The scenarios suggest that AI could help ease labour shortages and raise productivity, although effects vary substantially across subsectors and types of organisation. The results are scenarios, not forecasts.

Article (without peer review)

DAIOE: Dynamic AI Occupational Exposure (dataset and construction pipeline)

E. Engberg, H. Görg, M. Hellsten, F. Javed, M. Lodefalk, M. Längkvist, N. Monteiro, H. Kyvik Nordås, G. Pulito, S. Schroeder & A. Tang

Publication year

2026

Published in

Zenodo

Abstract

DAIOE is a dataset of occupation-year measures of exposure to artificial intelligence, accompanied by its construction pipeline and documentation. The index combines progress across public AI benchmarks with occupational ability profiles to estimate how exposure changes over time. The dataset covers multiple occupational classifications, including Swedish SSYK. It is a research data resource, not a peer-reviewed article.

Reports

Who is afraid of AI? Who should be?

Engberg, E., Görg, H., Hellsten, M., Javed, F., Lodefalk, M., Längkvist, M., & ..

Publication year

2026

Published in

Kiel Policy Brief, 2026.

Abstract

  • Occupations that are highly cognitive, non-physical, and low in social interaction — typically higher-skill white-collar roles such as data analysts, software developers, and translators — turn out to be highly AI-exposed
  • Occupations requiring manual dexterity or intensive interpersonal contact — such as construction labourers or nursing aides — remain among the least exposed to current AI technologies
  • Aggregate occupational exposure to AI has risen markedly since 2010, with especially rapid gains in the late 2010s and early 2020s
  • Our baseline estimates show no detectable effect of AI exposure on total firm employment, while it is associated with clear skill upgrading
      • Engberg, E., Görg, H., Hellsten, M., Javed, F., Lodefalk, M., Längkvist, M., & .. (2026). Who is afraid of AI? Who should be?. Kiel Policy Brief, 2026.
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