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

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  • 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
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    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. 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.
    3. 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.
    4. David Autor, 2024. "Applying AI to Rebuild Middle Class Jobs," NBER Working Papers 32140, National Bureau of Economic Research, Inc.
    5. 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.
    6. Spencer Bastani & Daniel Waldenström, 2024. "AI, automation and taxation," Chapters, in: Stéphane Carcillo & Stefano Scarpetta (ed.), Handbook on Labour Markets in Transition, chapter 19, pages 354-370, Edward Elgar Publishing.
    7. 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.
    8. 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.
    9. 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.
    10. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    11. 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.
    12. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    13. 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.
    14. repec:hal:pseose:halshs-01109372 is not listed on IDEAS
    15. 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..
    16. 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).
    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.
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    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

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