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Robots and Workers: Evidence from the Netherlands

Author

Listed:
  • Acemoglu, Daron

    (MIT)

  • Koster, Hans R.A.

    (Vrije Universiteit Amsterdam)

  • Ozgen, Ceren

    (University of Birmingham)

Abstract

We estimate the effects of robot adoption on firm-level and worker-level outcomes in the Netherlands using a large employer-employee panel dataset spanning 2009-2020. Our firm-level results confirm previous findings, with positive effects on value added and hours worked for robot-adopting firms and negative outcomes on competitors in the same industry. Our worker-level results show that directly-affected workers (e.g., bluecollar workers performing routine or replaceable tasks) face lower earnings and employment rates, while other workers indirectly gain from robot adoption. We also find that the negative effects from competitors' robot adoption load on directly-affected workers, while other workers benefit from this industry-level robot adoption. Overall, our results highlight the uneven effects of automation on the workforce.

Suggested Citation

  • Acemoglu, Daron & Koster, Hans R.A. & Ozgen, Ceren, 2023. "Robots and Workers: Evidence from the Netherlands," IZA Discussion Papers 15997, IZA Network @ LISER.
    • Handle: RePEc:iza:izadps:dp15997
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    References listed on IDEAS

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    1. Daron Acemoglu & Claire Lelarge & Pascual Restrepo, 2020. "Competing with Robots: Firm-Level Evidence from France," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 383-388, May.
    2. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    3. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    4. Adrian Adermon & Magnus Gustavsson, 2015. "Job Polarization and Task-Biased Technological Change: Evidence from Sweden, 1975–2005," Scandinavian Journal of Economics, Wiley Blackwell, vol. 117(3), pages 878-917, July.
    5. Matthias Kehrig & Nicolas Vincent, 2021. "The Micro-Level Anatomy of the Labor Share Decline," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(2), pages 1031-1087.
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    Keywords

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    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • 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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