IDEAS home Printed from https://ideas.repec.org/p/wiw/wus005/68239150.html
   My bibliography  Save this paper

Unslicing the pie: AI innovation and the labor share in European regions

Author

Listed:
  • Minniti, Antonio
  • Prettner, Klaus
  • Venturini, Francesco

Abstract

We study how the development of Artificial Intelligence (AI) influences the distribution of income between capital and labor and how this, in turn, exacerbates geographic income inequality. To investigate this issue, we first build a theoretical framework and then analyze data from European regions dating back to 2000. We find that for every doubling of regional AI innovation, there is a 0.7% to 1.6% decline in the labor share, which may have decreased by between 0.20 and 0.46 percentage points from a mean of 52% due solely to AI. This new technology is particularly detrimental to high-skill and medium-skill labor. The impact on income distribution is driven by worsening wage and employment conditions for high-skill labor, and by wage compression for medium- and low-skill labor. The effect of AI is not driven by other factors affecting regional development in Europe, nor by the concentration process in the AI market.

Suggested Citation

  • Minniti, Antonio & Prettner, Klaus & Venturini, Francesco, 2024. "Unslicing the pie: AI innovation and the labor share in European regions," Department of Economics Working Paper Series 369, WU Vienna University of Economics and Business.
    • Handle: RePEc:wiw:wus005:68239150
    as

    Download full text from publisher

    File URL: https://research.wu.ac.at/en/publications/42db2bf4-07a0-4cea-8aab-ea40f1f71b29
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    2. David Autor, 2024. "Applying AI to Rebuild Middle Class Jobs," NBER Working Papers 32140, National Bureau of Economic Research, Inc.
    3. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    4. Facundo Alvaredo & Bertrand Garbinti & Thomas Piketty, 2017. "On the Share of Inheritance in Aggregate Wealth: Europe and the USA, 1900–2010," Economica, London School of Economics and Political Science, vol. 84(334), pages 239-260, April.
    5. Bengtsson, Erik & Waldenström, Daniel, 2018. "Capital Shares and Income Inequality: Evidence from the Long Run," The Journal of Economic History, Cambridge University Press, vol. 78(3), pages 712-743, September.
    6. Spencer Bastani & Daniel Waldenström, 2024. "AI, Automation and Taxation," CESifo Working Paper Series 11084, CESifo.
    7. Charles I. Jones & Jihee Kim, 2018. "A Schumpeterian Model of Top Income Inequality," Journal of Political Economy, University of Chicago Press, vol. 126(5), pages 1785-1826.
    8. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    9. Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2022. "Artificial intelligence and industrial innovation: Evidence from German firm-level data," Research Policy, Elsevier, vol. 51(7).
    10. Ufuk Akcigit & John Grigsby & Tom Nicholas, 2017. "The Rise of American Ingenuity: Innovation and Inventors of the Golden Age," Working Papers 2017-6, Princeton University. Economics Department..
    11. Bastani, Spencer & Waldenström, Daniel, 2024. "AI, Automation and Taxation," IZA Policy Papers 212, Institute of Labor Economics (IZA).
    12. Guy Michaels & Ashwini Natraj & John Van Reenen, 2010. "Has ICT Polarized Skill Demand? Evidence from Eleven Countries over 25 Years," CEP Discussion Papers dp0987, Centre for Economic Performance, LSE.
    13. Dominique Guellec, 2020. "Digital Innovation and the Distribution of Income," NBER Chapters, in: Measuring and Accounting for Innovation in the Twenty-First Century, pages 323-370, National Bureau of Economic Research, Inc.
    14. Bastani, Spencer & Waldenström, Daniel, 2024. "AI, Automation, and Taxation," Working Paper Series 1501, Research Institute of Industrial Economics.
    15. Arindrajit Dube & Daniele Girardi & Òscar Jordà & Alan M. Taylor, 2023. "A Local Projections Approach to Difference-in-Differences," NBER Working Papers 31184, National Bureau of Economic Research, Inc.
    16. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    17. Lea Samek & Mariagrazia Squicciarini & Emile Cammeraat, 2021. "The human capital behind AI: Jobs and skills demand from online job postings," OECD Science, Technology and Industry Policy Papers 120, OECD Publishing.
    18. Venturini, Francesco, 2022. "Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 220-243.
    19. Guy Michaels & Ashwini Natraj & John Van Reenen, 2014. "Has ICT Polarized Skill Demand? Evidence from Eleven Countries over Twenty-Five Years," The Review of Economics and Statistics, MIT Press, vol. 96(1), pages 60-77, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Björn Döhring & Atanas Hristov & Christoph Maier & Werner Roeger & Anna Thum-Thysen, 2021. "COVID-19 acceleration in digitalisation, aggregate productivity growth and the functional income distribution," International Economics and Economic Policy, Springer, vol. 18(3), pages 571-604, July.
    2. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    3. Usabiaga, Carlos & Núñez, Fernando & Arendt, Lukasz & Gałecka-Burdziak, Ewa & Pater, Robert, 2022. "Skill requirements and labour polarisation: An association analysis based on Polish online job offers," Economic Modelling, Elsevier, vol. 115(C).
    4. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy & Marco Vivarelli, 2024. "AI as a new emerging technological paradigm: evidence from global patenting," DISCE - Quaderni del Dipartimento di Politica Economica dipe0038, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    5. Fossen, Frank M. & McLemore, Trevor & Sorgner, Alina, 2024. "Artificial Intelligence and Entrepreneurship," IZA Discussion Papers 17055, Institute of Labor Economics (IZA).
    6. Saam Marianne, 2024. "The Impact of Artificial Intelligence on Productivity and Employment – How Can We Assess It and What Can We Observe?," Intereconomics: Review of European Economic Policy, Sciendo, vol. 59(1), pages 22-27, February.
    7. Mr. Adrian Peralta & Agustin Roitman, 2018. "Technology and the Future of Work," IMF Working Papers 2018/207, International Monetary Fund.
    8. Alessia Lo Turco & Alessandro Sterlacchini, 2024. "Factors Enhancing Ai Adoption By Firms. Evidence From France," Working Papers 486, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    9. Luo, Kang & Liu, Yaobin & Chen, Pei-Fen & Zeng, Mingli, 2022. "Assessing the impact of digital economy on green development efficiency in the Yangtze River Economic Belt," Energy Economics, Elsevier, vol. 112(C).
    10. Damioli, Giacomo & Van Roy, Vincent & Vertesy, Daniel & Vivarelli, Marco, 2024. "Is Artificial Intelligence Generating a New Paradigm? Evidence from the Emerging Phase," IZA Discussion Papers 17183, Institute of Labor Economics (IZA).
    11. Cavenaile, Laurent, 2021. "Offshoring, computerization, labor market polarization and top income inequality," Journal of Macroeconomics, Elsevier, vol. 69(C).
    12. Schulte, Patrick, 2015. "Does skill-biased technical change diffuse internationally?," ZEW Discussion Papers 15-088, ZEW - Leibniz Centre for European Economic Research.
    13. Loebbing, Jonas, 2018. "An Elementary Theory of Endogenous Technical Change and Wage Inequality," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181603, Verein für Socialpolitik / German Economic Association.
    14. Nicholas Bloom & Tarek Alexander Hassan & Aakash Kalyani & Josh Lerner & Ahmed Tahoun, 2021. "The diffusion of disruptive technologies," CEP Discussion Papers dp1798, Centre for Economic Performance, LSE.
    15. Marelli Enrico & Sciulli Dario & Signorelli Marcello, 2014. "Skill mismatch of graduates in a local labour market," Экономика региона, CyberLeninka;Федеральное государственное бюджетное учреждение науки «Институт экономики Уральского отделения Российской академии наук», issue 2, pages 181-194.
    16. Naudé, Wim & Nagler, Paula, 2022. "The Ossified Economy: The Case of Germany, 1870-2020," IZA Discussion Papers 15607, Institute of Labor Economics (IZA).
    17. Barth, Erling & Davis, James C. & Freeman, Richard B. & McElheran, Kristina, 2023. "Twisting the demand curve: Digitalization and the older workforce," Journal of Econometrics, Elsevier, vol. 233(2), pages 443-467.
    18. Alexander Bick & Adam Blandin & David Deming, 2023. "The Rapid Adoption of Generative AI," On the Economy 98843, Federal Reserve Bank of St. Louis.
    19. Morgan Raux, 2019. "Looking for the "Best and Brightest": Hiring difficulties and high-skilled foreign workers," Working Papers halshs-02364921, HAL.
    20. T. Gries & R. Grundmann & I. Palnau & M. Redlin, 2017. "Innovations, growth and participation in advanced economies - a review of major concepts and findings," International Economics and Economic Policy, Springer, vol. 14(2), pages 293-351, April.

    More about this item

    Keywords

    Artificial Intelligence; patenting; labor share; European regions;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:wiw:wus005:68239150. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: WU Library (email available below). General contact details of provider: https://research.wu.ac.at/ .

    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.