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Temporary expats for exports: micro-level evidence

Abstract

We analyze the relation between temporary expats in firms and exports, exploiting micro-level panel data on migration and trade. Temporary expats are positively associated with exports. Their link with export intensity is larger for services than for merchandise and for exports of differentiated services and merchandise than for exports of homogeneous products. Our evidence also suggests that temporary expats are positively related to exports by assisting firms in overcoming informal destination-specific barriers. Overall, our findings suggest the importance of the temporary movement of persons for providing firms with up-to-date links to export markets.

Lodefalk, M. (2016). Temporary expats for exports: micro-level evidence. Review of World Economics, 152(4), 733-772. DOI: 10.1007/s10290-016-0254-0

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Author: Lodefalk, M.
Publication year: 2016
Published in: Review of World Economics

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Associate Professor
Magnus Lodefalk
magnus.lodefalk@oru.se

Similar content

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.

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.

Publication year

2026

Published in

Ratio Working Paper Series.

Abstract

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.

Working Paper No. 380. Artificial Intelligence, hiring and employment: Job postings evidence from Sweden.

Engberg, E., Hellsten, M., Javed, F., Lodefalk, M., Sabolová, R., Schroeder, S.

Publication year

2024

Published in

Ratio Working Paper Series.

Abstract

This paper investigates the impact of artificial intelligence (AI) on hiring and employment, using the universe of job postings published by the Swedish Public Employment Service from 2014-2022 and universal register data for Sweden. We construct a detailed measure of AI exposure according to occupational content and find that establishments exposed to AI are more likely to hire AI workers. Survey data further indicate that AI exposure aligns with greater use of AI services. Importantly, rather than displacing non-AI workers, AI exposure is positively associated with increased hiring for both AI and non-AI roles. In the absence of substantial productivity gains that might account for this increase, we interpret the positive link between AI exposure and non-AI hiring as evidence that establishments are using AI to augment existing roles and expand task capabilities, rather than to replace non-AI workers.