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Markets for jobs and their task overlap

Author

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  • Goos, Maarten
  • Rademakers, Emilie
  • Salomons, Anna
  • Willekens, Bert

Abstract

We show that tightness in markets for jobs for which an unemployed job seeker fully qualifies in terms of her task competencies is predictive of her unemployment duration. This suggests that the labour market is organized along jobs and their task content. We also find that unemployed job seekers do not compete in markets where they possess only part of the required task competencies, suggesting that task overlap across jobs is unimportant for worker mobility between job markets. This implies that adverse task-biased shocks are likely to have pronounced distributional consequences across workers with different task competencies. To illustrate this, we quantify the impact of technological progress that automates routine tasks, showing that this imposes substantial adjustment costs that are highly unevenly distributed across unemployed job seekers with routine versus non-routine task competencies.

Suggested Citation

  • Goos, Maarten & Rademakers, Emilie & Salomons, Anna & Willekens, Bert, 2019. "Markets for jobs and their task overlap," Labour Economics, Elsevier, vol. 61(C).
  • Handle: RePEc:eee:labeco:v:61:y:2019:i:c:s0927537119300764
    DOI: 10.1016/j.labeco.2019.101750
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    Cited by:

    1. Schmidpeter, Bernhard & Winter-Ebmer, Rudolf, 2021. "Automation, unemployment, and the role of labor market training," European Economic Review, Elsevier, vol. 137(C).
    2. Dabed, Diego & Genz, Sabrina & Rademakers, Emilie, 2025. "Equalising the effects of automation? The role of task overlap for job finding," Labour Economics, Elsevier, vol. 96(C).
    3. Marcel Steffen Eckardt, 2022. "Minimum wages in an automating economy," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(1), pages 58-91, February.
    4. Goos, Maarten & Rademakers, Emilie & Röttger, Ronja, 2021. "Routine-Biased technical change: Individual-Level evidence from a plant closure," Research Policy, Elsevier, vol. 50(7).
    5. Azio Barani, 2021. "Innovazione tecnologica e lavoro: automazione, occupazione e impatti socio-economici," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 0(114), pages 51-79.
    6. Fumagalli, Elena & Rezaei, Sarah & Salomons, Anna, 2022. "OK computer: Worker perceptions of algorithmic recruitment," Research Policy, Elsevier, vol. 51(2).
    7. Diego Dabed Sitnisky & Sabrina Genz & Emilie Rademakers, 2023. "Resilience to Automation: The Role of Task Overlap for Job Finding," Working Papers 2312, Utrecht School of Economics.
    8. Yashiv, Eran, 2021. "Moving from a poor economy to a rich one: A job tasks approach," Labour Economics, Elsevier, vol. 72(C).

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    More about this item

    Keywords

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    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • 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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