IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/110973.html

Can Artificial Intelligence Reduce Regional Inequality? Evidence from China

Author

Listed:
  • Li, Shiyuan
  • Hao, Miao

Abstract

Based on the analysis of provincial-level data from 2001 to 2015, we find that regional inequality in China is not optimistic. Whether artificial intelligence, as a major technological change, will improve or worsen regional inequality is worthy of researching. We divide regional inequality into two dimensions: production and consumption, a total of three indicators. The empirical research is carried out to the eastern, central and western regions respectively. It is found that industrial intelligence improves the inequality of residents’ consumer welfare among regions, while at the same time there is the possibility of worsening regional inequality of innovation. We also clarify the heterogeneity of the mechanisms that artificial intelligence promotes innovation in different regions.

Suggested Citation

  • Li, Shiyuan & Hao, Miao, 2021. "Can Artificial Intelligence Reduce Regional Inequality? Evidence from China," MPRA Paper 110973, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:110973
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/110973/1/MPRA_paper_110973.pdf
    File Function: original version
    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. Maarten Goos & Alan Manning & Anna Salomons, 2009. "Job Polarization in Europe," American Economic Review, American Economic Association, vol. 99(2), pages 58-63, May.
    3. Chi‐Young Choi & Horag Choi & Alexander Chudik, 2020. "Regional inequality in the U.S.: Evidence from city‐level purchasing power," Journal of Regional Science, Wiley Blackwell, vol. 60(4), pages 738-774, September.
    4. David Hémous & Morten Olsen, 2022. "The Rise of the Machines: Automation, Horizontal Innovation, and Income Inequality," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(1), pages 179-223, January.
    5. Maarten Goos & Alan Manning, 2007. "Lousy and Lovely Jobs: The Rising Polarization of Work in Britain," The Review of Economics and Statistics, MIT Press, vol. 89(1), pages 118-133, February.
    6. Katz, Lawrence F. & Autor, David H., 1999. "Changes in the wage structure and earnings inequality," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 26, pages 1463-1555, Elsevier.
    7. William D. Nordhaus, 2021. "Are We Approaching an Economic Singularity? Information Technology and the Future of Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 299-332, January.
    8. Robert E. Hall & Charles I. Jones, 1999. "Why do Some Countries Produce So Much More Output Per Worker than Others?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 83-116.
    9. Jeffrey D. Sachs & Laurence J. Kotlikoff, 2012. "Smart Machines and Long-Term Misery," NBER Working Papers 18629, National Bureau of Economic Research, Inc.
    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. Filippo Bertani & Marco Raberto & Andrea Teglio, 2020. "The productivity and unemployment effects of the digital transformation: an empirical and modelling assessment," Review of Evolutionary Political Economy, Springer, vol. 1(3), pages 329-355, November.
    2. Gries, T. & Grundmann, R. & Palnau, I. & Redlin, M., 2015. "Does technological change drive inclusive industrialization? : A review of major concepts and findings," MERIT Working Papers 2015-044, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    3. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    4. 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.
    5. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    6. Salomons, Anna & vom Baur, Cäcilia & Zierahn-Weilage, Ulrich, 2025. "Expertise at Work: New Technologies, New Skills, and Worker Impacts," IZA Discussion Papers 18248, Institute of Labor Economics (IZA).
    7. Rod Tyers & Yixiao Zhou, 2023. "Automation and inequality with taxes and transfers," Scottish Journal of Political Economy, Scottish Economic Society, vol. 70(1), pages 68-100, February.
    8. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    9. Nieddu, Marcello & Bertani, Filippo & Ponta, Linda, 2021. "Sustainability transition and digital trasformation: an agent-based perspective," MPRA Paper 106943, University Library of Munich, Germany.
    10. Gravina, Antonio Francesco & Foster-McGregor, Neil, 2020. "Automation, globalisation and relative wages: An empirical analysis of winners and losers," MERIT Working Papers 2020-040, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    11. Joanne Lindley & Stephen Machin, 2011. "Rising Wage Inequality and Postgraduate Education," CEP Discussion Papers dp1075, Centre for Economic Performance, LSE.
    12. Dawson, John W. & Sturgill, Brad, 2022. "Market Institutions and Factor Shares Across Countries," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 266-289.
    13. Lipowski, Cäcilia & Salomons, Anna & Zierahn-Weilage, Ulrich, 2024. "Expertise at work: New technologies, new skills, and worker impacts," ZEW Discussion Papers 24-044, ZEW - Leibniz Centre for European Economic Research.
    14. Ljubica Nedelkoska & Frank Neffke, 2019. "Skill Mismatch and Skill Transferability: Review of Concepts and Measurements," Papers in Evolutionary Economic Geography (PEEG) 1921, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2019.
    15. Ljubica Nedelkoska & Simon Wiederhold, 2010. "Technology, outsourcing, and the demand for heterogeneous labor: Exploring the industry dimension," Jena Economics Research Papers 2010-052, Friedrich-Schiller-University Jena.
    16. Ge, Suqin & Zhou, Yu, 2020. "Robots, computers, and the gender wage gap," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 194-222.
    17. Andreas Eder & Wolfgang Koller & Bernhard Mahlberg, 2024. "The contribution of industrial robots to labor productivity growth and economic convergence: a production frontier approach," Journal of Productivity Analysis, Springer, vol. 61(2), pages 157-181, April.
    18. Alonso, Cristian & Berg, Andrew & Kothari, Siddharth & Papageorgiou, Chris & Rehman, Sidra, 2022. "Will the AI revolution cause a great divergence?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 18-37.
    19. Stephan Kampelmann & François Rycx, 2013. "The Dynamics Of Task-Biased Technological Change :The Case Of Occupations," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 56(2), pages 113-142.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

    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:pra:mprapa:110973. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.