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Job Automation Risk, Economic Structure and Trade: a European Perspective

Author

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  • Foster-McGregor, Neil
  • Nomaler, Önder
  • Verspagen, Bart
Abstract
Recent studies report that technological developments in machine learning and artificial intelligence present a significant risk to jobs in advanced countries. We re-estimate automation risk at the job level, finding sectoral employment structure to be key in determining automation risk at the country level. At the country level, we find a negative relationship between automation risk and labour productivity. We then analyse the role of trade as a factor leading to structural changes and consider the relation between trade and aggregate automation risk by comparing automation risk between a hypothetical autarky and the actual situation. Results indicate that with trade, automation risk is higher in Europe, although moderately so. Automation risk in the high-productivity European countries is higher with trade, with trade between European and non-European nations driving these results. This implies that these countries do not, on balance, offshore automation risk, but rather import it. The sectors that show the largest automation risk relation to trade are manufacturing, trade, transport and finance.

Suggested Citation

  • Foster-McGregor, Neil & Nomaler, Önder & Verspagen, Bart, 2021. "Job Automation Risk, Economic Structure and Trade: a European Perspective," Research Policy, Elsevier, vol. 50(7).
    • Handle: RePEc:eee:respol:v:50:y:2021:i:7:s004873332100072x
    DOI: 10.1016/j.respol.2021.104269
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    Cited by:

    1. Cresti, Lorenzo & Dosi, Giovanni & Fagiolo, Giorgio, 2023. "Technological interdependencies and employment changes in European industries," Structural Change and Economic Dynamics, Elsevier, vol. 64(C), pages 41-57.
    2. Florencia Jaccoud & Fabien Petit & Tommaso Ciarli & Maria Savona, 2024. "Automation and Employment over the Technology Life Cycle: Evidence from European Regions," CEPEO Working Paper Series 24-02, UCL Centre for Education Policy and Equalising Opportunities, revised Feb 2024.
    3. Nii-Aponsah, Hubert, 2022. "Automation exposure and implications in advanced and developing countries across gender, age, and skills," MERIT Working Papers 2022-021, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    4. Filippi, Emilia & Bannò, Mariasole & Trento, Sandro, 2023. "Automation technologies and their impact on employment: A review, synthesis and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    5. Stahl, Bernd Carsten & Brooks, Laurence & Hatzakis, Tally & Santiago, Nicole & Wright, David, 2023. "Exploring ethics and human rights in artificial intelligence – A Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    6. Antonio Martins-Neto & Nanditha Mathew & Pierre Mohnen & Tania Treibich, 2024. "Is There Job Polarization in Developing Economies? A Review and Outlook," The World Bank Research Observer, World Bank, vol. 39(2), pages 259-288.

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    More about this item

    Keywords

    Automation risk for employment; Sectoral Employment Structure; Industry 4.0; Globalization; Global Value Chains JEL Codes: F16; F66; O33; J24;
    All these keywords.

    JEL classification:

    • F16 - International Economics - - Trade - - - Trade and Labor Market Interactions
    • F66 - International Economics - - Economic Impacts of Globalization - - - Labor
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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