The hidden costs of technological change: investigating pathways through which highly automatable jobs undermine workers’ health in Germany

Mariia Vasiakina and Christian Dudel
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Mariia Vasiakina: Max Planck Institute for Demographic Research, Rostock, Germany
Christian Dudel: Max Planck Institute for Demographic Research, Rostock, Germany

No WP-2025-032, MPIDR Working Papers from Max Planck Institute for Demographic Research, Rostock, Germany

Abstract: The ongoing economic transformation driven by automation has significant social implications, particularly for the health and well-being of workers who face the risk of job displacement and the pressure to acquire new skills and qualifications. However, the specific pathways through which exposure to automation risk affects health outcomes remain poorly understood, and the relative contribution of each potential mechanism is still unclear. In this study, we examine the nature of the relationship between high workplace exposure to automation risk and a range of subjective health outcomes – including self-reported health, anxiety, and both physical and mental component summary scores from the SF-12 Health Survey – among workers in Germany. Using data from the German Socio-Economic Panel (SOEP) linked with administrative records from the Occupational Panel for Germany (2014–2022), we apply the Karlson-Holm-Breen (KHB) mediation analysis method to assess whether broader indicators of economic uncertainty, alongside automation-specific factors, mediate the relationship between high automation risk and workers’ health. Our results indicate that the negative impact of high automation risk on health in Germany primarily operates through indirect pathways (related to mediators) for both genders, with the exception of physical health among male workers, where a direct negative effect is also evident. Economic concerns – particularly job insecurity and worries about one’s future financial situation – emerge as more significant mediators than automation-specific factors. Overall, our findings suggest that the mechanisms linking high automation risk to health are gender- and context-sensitive, and are shaped by broader economic conditions and workplace environments.

Keywords: Germany; automation; health; risk exposure; technological change (search for similar items in EconPapers)
JEL-codes: J1 Z0 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2025
New Economics Papers: this item is included in nep-eur, nep-hea, nep-lab, nep-ltv and nep-tid
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Persistent link: https://EconPapers.repec.org/RePEc:dem:wpaper:wp-2025-032

DOI: 10.4054/MPIDR-WP-2025-032

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