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Selected publication

Absolute income mobility and the effect of parent generation inequality: An extended decomposition approach
Liss, E., Korpi, M., & Wennberg, K.
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Publications

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  • Publications

Selected publication

No evidence of counteracting policy effects on European solar power invention and diffusion
Grafström, J., & Poudineh, R.
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About

  • About us

    • About
    • Contact us

  • Media

    • News archive

  • Cooperations

    • Eli F. Heckscher Lectures

Research

  • Areas

    • Labour Market Research
    • Competitiveness Research
    • Climate and Environmental Research

  • Ongoing research

    • Working Paper Series
  • People

    • Publications

    • Publications

      • Publications

    Artificial Intelligence and Worker Stress Evidence from Germany

    PublicationArticle (with peer review)
    Magnus Lodefalk
    Artificial Intelligence and Worker Stress Evidence from
    Download

    Abstract

    We use individual survey data providing detailed information on stress, technology adoption, and work, worker, and employer characteristics, in combination with recent measures of AI and robot exposure, to investigate how new technologies affect worker stress. We find a persistent negative relationship, suggesting that AI and robots could reduce the stress level of workers in Germany. We furthermore provide evidence on potential mechanisms to explain our findings. Overall, the paper contributes to the economic literature by providing suggestive evidence of modern technologies changing the way we perform our work in a way that reduces stress and work pressure.

    Koch, M., & Lodefalk, M. (2025). Artificial Intelligence and Worker Stress: Evidence from Germany Digital Society, 4(1), 5

    Details

    Author

    Koch, M., & Lodefalk, M.

    Publication year

    2025

    Published in

    Digital Society, 4(1), 5

    Related

    Magnus Lodefalk
    Associate Professor

    magnus.lodefalk@oru.se

    Similar content

    Artificial Intelligence for Public Use
    Working paperPublication
    Lodefalk, M.; Engberg, E.; Lidskog, R.; Tang, A.
    Download
    Publication year

    2025

    Published in

    Örebro University School of Business Working Paper

    Abstract

    This paper investigates the economic and societal impacts of Artificial Intelligence (AI) in the public sector, focusing on its potential to enhance productivity and mitigate labour shortages. Employing detailed administrative data and novel occupational exposure measures, we simulate future scenarios over a 20-year horizon, using Sweden as an illustrative case. Our findings indicate that advances in AI development and uptake could significantly alleviate projected labour shortages and enhance productivity. However, outcomes vary substantially across sectors and organisational types, driven by differing workforce compositions. Complementing the economic analysis, we identify key challenges that hinder AI’s effective deployment, including technical limitations, organisational barriers, regulatory ambiguity, and ethical risks such as algorithmic bias and lack of transparency. Drawing from an interdisciplinary conceptual framework, we argue that AI’s integration in the public sector must address these socio-technical and institutional factors comprehensively. To unlock AI’s full potential, substantial investments in technological infrastructure, human capital development, regulatory clarity, and robust governance mechanisms are essential. Our study thus contributes both novel economic evidence and an integrated societal perspective, informing strategies for sustainable and equitable public-sector digitalisation.

    Artificial intelligence, hiring and employment: job postings evidence from Sweden
    Article (with peer review)Publication
    Engberg, E., Hellsten, M., Javed, F., Lodefalk, M., Sabolová, R., Schroeder, S., & Tang, A
    Publication year

    2025

    Published in

     Applied Economics Letters

    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 to 2022 and full-population administrative data for Sweden. We exploit 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.

    Immigrant employment and the contract enforcement costs of offshoring
    Article (with peer review)Publication
    Hatzigeorgiou, A., Karpaty, P., Kneller, R., & Lodefalk, M.
    Download
    Publication year

    2024

    Published in

    Review of World Economics, 1-29.

    Abstract

    Offshoring continues to be an important dimension of firms’ internationalization choices. However, offshoring also increases contract enforcement costs by inhibiting the coordination and monitoring of performance. Immigrant employees may reduce such costs through their specific knowledge of the employer, their country of birth and access to foreign networks. In this paper, we investigate the role of immigrant employees within firms on firm offshoring, employing rich administrative Swedish microlevel data that include specific information about the characteristics of employees, manufacturing firms and their bilateral offshoring. Our results support the hypothesis that immigrant employees increase offshoring by lowering contract enforcement costs. Hiring one additional immigrant employee is linked to a relatively larger increase in offshoring at the intensive than the extensive margin, on average. The association to offshoring is considerably stronger for skilled immigrant employees and for contract and R&D intensive offshoring. Instrumental variable estimations demonstrate qualitatively similar results, while a placebo test with randomized immigrant employment does not generate any link between immigrants and offshoring.

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