Hiring value of skill signals in occupations with different automation risks: evidence from a survey experiment in Germany

Benjamin Schimke
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Benjamin Schimke: Department of Empirical Educational Research, Institute for Educational Research, School of Education, University of Wuppertal, Wuppertal, Germany

Journal for Labour Market Research, 2026, vol. 60

Abstract: "Technological change is transforming occupational tasks across modern labour markets, affecting employment security and (re-)employment chances. To maintain their labour market opportunities, affected workers must adapt by acquiring new skills, primarily through further education. This study examines the hiring value of such training in occupations with varying susceptibility to task automation. A factorial survey experiment was conducted with 717 HR managers and recruiters in Germany, generating 5,443 evaluations of fictitious CV-like profiles against job advertisements in 15 occupations. Results show that certificates for further training directly related to advertised tasks increase interview probabilities, but this effect declines with higher occupational automation risk. By contrast, identical signals based on prior work experience remain unaffected by automation risk and the same training devaluation rate is found for training courses not directly related to demanded skills. These findings suggest that the perceived value of further training is shaped not only by skill relevance, but especially that a potential lack of proven application in real-world contexts may function as weaker labor market signals in highly automatable occupations. The study highlights the differential role of skill signals in recruitment and contributes to research on labor market adaptation to technological change." (Author's abstract, IAB-Doku) ((en))

Keywords: Bundesrepublik Deutschland; Weiterbildungsbeteiligung; Auswirkungen; Automatisierung; Berufserfahrung; Berufsgruppe; Bildungsertrag; Kompetenzbewertung; Personalauswahl; Qualifikationsnachweis; Risiko; Substitutionspotenzial; technischer Wandel; Arbeitsmarktchancen; Arbeitsuchende; Arbeitszeugnis; 2021-2022 (search for similar items in EconPapers)
JEL-codes: J24 J62 M51 M53 O15 O33 (search for similar items in EconPapers)
Date: 2026-06-26
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DOI: 10.1186/s12651-026-00433-5

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