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Worker Personality: Another Skill Bias beyond Education in the Digital Age

Author

Listed:
  • Eckhardt Bode
  • Stephan Brunow
  • Ingrid Ott
  • Alina Sorgner

Abstract

We present empirical evidence suggesting that technological progress in the digital age will be biased not only with respect to skills acquired through education but additionally with respect to non‐cognitive skills (personality). We measure the direction of technological change by estimated future digitalization probabilities of occupations, and non‐cognitive skills by the Big Five personality traits from four German worker surveys. Even though we control for education and work experience, we find that workers who are more open to experience, emotionally more stable and less agreeable will tend to be less susceptible to digitalization. We also find that future technological progress may not continue to hollow out the middle class as much as it did in the recent past. These results suggest that education and labor market policies should put more emphasis on children's and workers’ personalities to strengthen their labor market resilience in the digital age.

Suggested Citation

  • Eckhardt Bode & Stephan Brunow & Ingrid Ott & Alina Sorgner, 2019. "Worker Personality: Another Skill Bias beyond Education in the Digital Age," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 254-294, November.
    • Handle: RePEc:bla:germec:v:20:y:2019:i:4:p:e254-e294
    DOI: 10.1111/geer.12165
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    Cited by:

    1. Tatiana V. Volchenko & Lyudmila S. Ruzhanskaya & Maxim A. Fokeev, 2021. "Non-cognitive skills of employees and their influence on voluntary turnover," Upravlenets, Ural State University of Economics, vol. 12(2), pages 87-101, April.
    2. Fossen, Frank M. & Sorgner, Alina, 2021. "Digitalization of work and entry into entrepreneurship," Journal of Business Research, Elsevier, vol. 125(C), pages 548-563.
    3. Dicks, Alexander & Künn-Nelen, Annemarie & Levels, Mark & Montizaan, Raymond, 2024. "Automation risks of vocational training programs and early careers in the Netherlands," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 67(4), pages 507-528.
    4. Maarten Goos & Melanie Arntz & Ulrich Zierahn & Terry Gregory & Stephanie Carretero Gomez & Ignacio Gonzalez Vazquez & Koen Jonkers, 2019. "The Impact of Technological Innovation on the Future of Work," JRC Working Papers on Labour, Education and Technology 2019-03, Joint Research Centre.
    5. Hübler, Olaf, 2017. "Health and weight – gender-specific linkages under heterogeneity, interdependence and resilience factors," Economics & Human Biology, Elsevier, vol. 26(C), pages 96-111.
    6. Sorgner, Alina & Bode, Eckhardt & Krieger-Boden, Christiane & Aneja, Urvashi & Coleman, Susan & Mishra, Vidisha & Robb, Alicia M., 2017. "The effects of digitalization on gender equaliy in the G20 economies: Women20 study," Kiel E-Books, Kiel Institute for the World Economy (IfW Kiel), number 170571.

    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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