IDEAS home Printed from https://ideas.repec.org/a/vrs/ceuecj/v11y2024i58p14n1001.html
   My bibliography  Save this article

The relationship between Artificial Intelligence (AI) exposure and returns to education

Author

Listed:
  • Madoń Karol

    (SGH Warsaw School of Economics, Al. Niepodległości 162, 02-554 Warsaw, Poland; Institute for Structural Research (IBS), Irysowa 18c, 02-660 Warsaw, Poland)

Abstract

This paper studies the relationship between exposure to artificial intelligence (AI) and workers’ wages across European countries. Overall, a positive relationship between exposure to AI and workers’ wages is found, however it differs considerably between workers and countries. High-skilled workers experience far higher wage premiums related to AI-related skills than middle- and low-skilled workers. Positive associations are concentrated among occupations moderately and highly exposed to AI (between the 6th and 9th decile of the exposure), and are weaker among the least exposed occupations. Returns of AI-related skills among high-skilled workers are even higher in Eastern European Countries compared to Western European countries. The heterogeneity likely originates from the difference in overall labour costs between country groups. The results presented in this study were obtained from the estimation of Mincerian wage regressions on the 2018 release of the EU Structure of Earning Survey.

Suggested Citation

  • Madoń Karol, 2024. "The relationship between Artificial Intelligence (AI) exposure and returns to education," Central European Economic Journal, Sciendo, vol. 11(58), pages 1-14.
    • Handle: RePEc:vrs:ceuecj:v:11:y:2024:i:58:p:14:n:1001
    DOI: 10.2478/ceej-2024-0029
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/ceej-2024-0029
    Download Restriction: no
    File URL: https://libkey.io/10.2478/ceej-2024-0029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    artificial intelligence; wages; technological change; Europe;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:ceuecj:v:11:y:2024:i:58:p:14:n:1001. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.