IDEAS home Printed from https://ideas.repec.org/p/zbw/ifwedp/201948.html
   My bibliography  Save this paper

The macroeconomic consequences of artificial intelligence: A theoretical framework

Author

Listed:
  • Huang, Xu
  • Hu, Yan
  • Dong, Zhiqiang

Abstract

The authors explore the impact of artificial intelligence on the economy by improving the neoclassical production function and the task-based model. Based on the capital accumulation of artificial intelligence and technological progress, they present a theoretical model that explores the effect of alternative and complementary artificial intelligence on wages, capital prices, labor share, capital share and economic growth. The model shows that artificial intelligence capital lowers the capital prices and increases wages. In addition, if artificial intelligence and labor force are complementary, artificial intelligence capital has a positive impact on labor share, but if artificial intelligence and labor force can substitute each other, labor share is negatively influenced by artificial intelligence capital. The authors extend the task-based model and find that technological progress increases both wages and labor share by generating new tasks. In the long run, without consideration of exogenous technology, as the artificial intelligence capital accumulates, per capita output, per capita traditional capital and per capita artificial intelligence capital grow at the same rate, and economic growth finally reaches steady state equili- brium. With exogenous technology considered, artificial intelligence technology improves, and sustained economic growth is achieved.

Suggested Citation

  • Huang, Xu & Hu, Yan & Dong, Zhiqiang, 2019. "The macroeconomic consequences of artificial intelligence: A theoretical framework," Economics Discussion Papers 2019-48, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwedp:201948
    as

    Download full text from publisher

    File URL: http://www.economics-ejournal.org/economics/discussionpapers/2019-48
    Download Restriction: no
    File URL: https://www.econstor.eu/bitstream/10419/203115/1/1676021787.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joseph Zeira, 1998. "Workers, Machines, and Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1091-1117.
    2. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    3. Prettner, Klaus & Strulik, Holger, 2017. "The lost race against the machine: Automation, education and inequality in an R&D-based growth model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 08-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    4. Seth G. Benzell & Laurence J. Kotlikoff & Guillermo LaGarda & Jeffrey D. Sachs, 2015. "Robots Are Us: Some Economics of Human Replacement," NBER Working Papers 20941, National Bureau of Economic Research, Inc.
    5. Gasteiger, Emanuel & Prettner, Klaus, 2017. "A note on automation, stagnation, and the implications of a robot tax," Discussion Papers 2017/17, Free University Berlin, School of Business & Economics.
    6. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    7. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    8. Seth G. Benzell & Laurence J. Kotlikoff & Guillermo LaGarda & Jeffrey D. Sachs, 2015. "Robots Are Us: Some Economics of Human Replacement," NBER Working Papers 20941, National Bureau of Economic Research, Inc.
    9. Gasteiger, Emanuel & Prettner, Klaus, 2022. "Automation, Stagnation, And The Implications Of A Robot Tax," Macroeconomic Dynamics, Cambridge University Press, vol. 26(1), pages 218-249, January.
    10. 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.
    11. DeCanio, Stephen J., 2016. "Robots and humans – complements or substitutes?," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 280-291.
    12. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kerstin Hotte & Angelos Theodorakopoulos & Pantelis Koutroumpis, 2021. "Automation and Taxation," Papers 2103.04111, arXiv.org, revised Apr 2022.

    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. Gries, Thomas & Naudé, Wim, 2020. "Artificial Intelligence, Income Distribution and Economic Growth," IZA Discussion Papers 13606, Institute of Labor Economics (IZA).
    2. Fierro, Luca Eduardo & Caiani, Alessandro & Russo, Alberto, 2022. "Automation, Job Polarisation, and Structural Change," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 499-535.
    3. Naude, Wim, 2019. "The race against the robots and the fallacy of the giant cheesecake: Immediate and imagined impacts of artificial intelligence," MERIT Working Papers 2019-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    4. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    5. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the digital divide: Workers' exposure to digitalization and its consequences for individual employment," Discussion Papers 118, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    6. Prettner, Klaus & Strulik, Holger, 2017. "The lost race against the machine: Automation, education and inequality in an R&D-based growth model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 08-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    7. Dario Cords & Klaus Prettner, 2022. "Technological unemployment revisited: automation in a search and matching framework [The future of work: meeting the global challenges of demographic change and automation]," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 115-135.
    8. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2019. "How can robots affect wage inequality?," Economic Modelling, Elsevier, vol. 81(C), pages 161-169.
    9. Gregory, Terry & Salomons, Anna & Zierahn, Ulrich, 2016. "Racing With or Against the Machine? Evidence from Europe," VfS Annual Conference 2016 (Augsburg): Demographic Change 145843, Verein für Socialpolitik / German Economic Association.
    10. Stähler, Nikolai, 2021. "The Impact of Aging and Automation on the Macroeconomy and Inequality," Journal of Macroeconomics, Elsevier, vol. 67(C).
    11. Abeliansky, Ana Lucia & Prettner, Klaus, 2017. "Automation and demographic change," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168215, Verein für Socialpolitik / German Economic Association.
    12. Mr. Andrew Berg & Lahcen Bounader & Nikolay Gueorguiev & Hiroaki Miyamoto & Mr. Kenji Moriyama & Ryota Nakatani & Luis-Felipe Zanna, 2021. "For the Benefit of All: Fiscal Policies and Equity-Efficiency Trade-offs in the Age of Automation," IMF Working Papers 2021/187, International Monetary Fund.
    13. Sasaki, Hiroaki & Hagiwara, Takefumi & Pham, Huong & Fukatani, Noriki & Ogawa, Shogo & Okahara, Naoto, 2021. "How Does Automation Affect Economic Growth and Income Distribution in a Two-Class Economy?," MPRA Paper 106481, University Library of Munich, Germany.
    14. Jean-Philippe Deranty & Thomas Corbin, 2022. "Artificial Intelligence and work: a critical review of recent research from the social sciences," Papers 2204.00419, arXiv.org.
    15. Heyman, Fredrik & Norbäck, Pehr-Johan & Persson, Lars, 2021. "Automation, Work and Productivity: The Role of Firm Heterogeneity," Working Paper Series 1382, Research Institute of Industrial Economics, revised 09 Mar 2023.
    16. ARAI Kosuke & FUJIWARA Ippei & SHIROTA Toyoichiro, 2021. "Robot Penetration and Task Changes," Discussion papers 21093, Research Institute of Economy, Trade and Industry (RIETI).
    17. Juan F. Jimeno, 2019. "Fewer babies and more robots: economic growth in a new era of demographic and technological changes," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 93-114, June.
    18. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    19. Ilona Pavlenkova & Luca Alfieri & Jaan Masso, 2021. "Effects Of Automation On The Gender Pay Gap: The Case Of Estonia," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 131, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    20. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.

    More about this item

    Keywords

    artificial intelligence; automation; economic growth; share of labor;
    All these keywords.

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    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:zbw:ifwedp:201948. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iwkiede.html .

    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.