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PublikationWorking paper

Working paper No. 302: Do Migrants Facilitate Internationalization? A Review of the Literature

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Sammanfattning

How migration relates to internationalization has been a prominent question in international economics for a long time and its relevance for policy has increased with the amplified political focus on migration. But the role of migration for internationalization is not as obvious as the standard theory suggests, and tightening migration could have unexpected consequences for both developing and developed countries. In this paper we review and discuss over 100 papers published about migrants’ role in international trade and foreign direct investment, from pioneering country-level studies to nascent firm-level studies that utilize employer-employee data. To our knowledge, this is the first paper offering a wide-ranging review of the different strands of theory on the relationship between migration and internationalization, as well as new empirical findings. Although the evidence suggests that migration can facilitate internationalization, we also note substantial gaps and inconsistencies in the extant literature. The aim of this paper is to encourage future research and assist policymakers in their efforts to promote internationalization, and better understand the economic effects of changes in migration policy.

Hatzigeorgiou, A. & Lodefalk, M. (2017). Do Migrants Facilitate Internationalization? A Review of the Literature. Working Paper no. 302. Stockholm: Ratio.


Liknande innehåll

Working paper

Who Adopts AI? Evidence on Firms, Technologies and Workers

Pulito, G., Pytlikova, M., Schroeder, S. & Lodefalk, M.

Publiceringsår

2026

Publicerat i

GLO Discussion Paper

Sammanfattning

Using two waves of nationally representative Danish firm surveys linked to employer–employee administrative registers, we study how adoption varies across artificial intelligence (AI) and related advanced technologies. We show that AI adoption is highly technology-specific. While firm size and digital infrastructure predict adoption broadly, workforce composition operates through distinct channels: STEM-educated workforces predict core AI adoption, whereas non-STEM university-educated workforces are associated with generative AI adoption, indicating different human capital complementarities. The factors associated with adoption differ from those predicting deployment breadth: firm size and digital maturity matter for both, whereas workforce composition primarily predicts adoption alone. Machine learning and natural language processing are deployed across multiple business functions, whereas other advanced technologies remain concentrated in specific operational domains. Individual-level evidence provides a foundation for these patterns, with awareness of workplace AI usage concentrated among managers and high-skilled workers. Self-reported AI knowledge is higher among younger and more educated individuals. Finally, commonly used occupational AI exposure measures vary substantially in their ability to predict observed adoption, with benchmark-based measures outperforming patent-based and large-language-model-focused alternatives. These findings show that treating AI as a monolithic category obscures economically meaningful variation in who adopts, what they deploy, and how well existing measures capture it.

Rapporter

Who is afraid of AI? Who should be?

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

Publiceringsår

2026

Publicerat i

Kiel Policy Brief, 2026.

Sammanfattning

  • 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
    1. 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.
    Working paper

    Ratio Working Paper No. 388: Same Storm, Different Boats: Generative AI and the Age Gradient in Hiring

    Lodefalk, M., Löthman, L., Koch, M., & Engberg, E.

    Publiceringsår

    2026

    Publicerat i

    Ratio Working Paper Series.

    Sammanfattning

    We show that the age composition of employment within Swedish employers shifts after the arrival of generative AI, with no corresponding reduction in aggregate labour demand. Using 4.6 million job advertisements from Sweden’s largest recruitment platform, we find that the broad decline in postings since 2022 aligns with monetary tightening rather than AI, exploiting Sweden’s seven-month gap between the Riksbank’s first rate hike and the launch of ChatGPT as a timing test. We then use full-population employer–employee register data and an employer-level difference-in-differences design to estimate how AI exposure affects employment composition across six age groups. An event study documents an accelerating decline in employment of 22–25-year-olds in high-AI-exposure occupations, reaching 5.5 per cent by early 2025 relative to less exposed occupations within the same employers, while employment of workers over 50 rose by 1.3 per cent. The widening age gradient suggests that generative AI reshapes hiring composition rather than aggregate demand, with the adjustment burden falling disproportionately on entry-level workers.

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    Detaljer

    Författare
    Hatzigeorgiou, A. & Lodefalk, M.
    Publiceringsår
    2017
    Publicerat i

    Ratio Working Paper

    Relaterat

    • Docent

      Magnus Lodefalk

      magnus.lodefalk@oru.se