IDEAS home Printed from https://ideas.repec.org/a/eee/ecanpo/v84y2024icp42-56.html
   My bibliography  Save this article

The application of industrial robots and changes in capital-labour income disparity in China

Author

Listed:
  • Zhang, Xinchun
  • Yu, Qi
  • Liu, Jianxu
  • He, Ying
  • Xu, Aijia

Abstract

The technological revolution, particularly the rise of industrial robots and artificial intelligence, has significantly impacted global economic growth and income disparity. This study examines the impact of industrial robot applications on the capital-labour income disparity in China, a country with the highest number of industrial robot applications and a commitment to reducing income inequality. The findings indicate that industrial robots intensify the income disparity between capital and labour, particularly in economically underdeveloped regions characterized by less sophisticated industrial structures, low levels of human capital, underdeveloped physical capital, and inadequate market economies. The promotion of industrial structure sophistication, enhancement of human capital levels, deepening of physical capital, and advancement of market development can mitigate the adverse impact of industrial robot applications on the income disparity between capital and labour. The study underscores the necessity of institutional reforms and targeted policies across these dimensions to address the negative impacts of new technologies.

Suggested Citation

  • Zhang, Xinchun & Yu, Qi & Liu, Jianxu & He, Ying & Xu, Aijia, 2024. "The application of industrial robots and changes in capital-labour income disparity in China," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 42-56.
    • Handle: RePEc:eee:ecanpo:v:84:y:2024:i:c:p:42-56
    DOI: 10.1016/j.eap.2024.08.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S031359262400208X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eap.2024.08.020?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ma, Hongmei & Gao, Qian & Li, Xiuzhen & Zhang, Yun, 2022. "AI development and employment skill structure: A case study of China," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 242-254.
    2. Per Krusell & Lee E. Ohanian & JosÈ-Victor RÌos-Rull & Giovanni L. Violante, 2000. "Capital-Skill Complementarity and Inequality: A Macroeconomic Analysis," Econometrica, Econometric Society, vol. 68(5), pages 1029-1054, September.
    3. Philip Bodman & Thanh Le, 2013. "Assessing the roles that absorptive capacity and economic distance play in the foreign direct investment-productivity growth nexus," Applied Economics, Taylor & Francis Journals, vol. 45(8), pages 1027-1039, March.
    4. Fujii, Hidemichi & Managi, Shunsuke, 2018. "Trends and priority shifts in artificial intelligence technology invention: A global patent analysis," Economic Analysis and Policy, Elsevier, vol. 58(C), pages 60-69.
    5. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    6. Daron Acemoglu, 1998. "Why Do New Technologies Complement Skills? Directed Technical Change and Wage Inequality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1055-1089.
    7. 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.
    8. Daron Acemoglu, 2002. "Directed Technical Change," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(4), pages 781-809.
    9. Daron Acemoglu & Pascual Restrepo, 2018. "Low-Skill and High-Skill Automation," Journal of Human Capital, University of Chicago Press, vol. 12(2), pages 204-232.
    10. Daron Acemoglu & Veronica Guerrieri, 2008. "Capital Deepening and Nonbalanced Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 116(3), pages 467-498, June.
    11. 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.
    12. 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.
    13. Mutascu, Mihai, 2021. "Artificial intelligence and unemployment: New insights," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 653-667.
    14. Daron Acemoglu, 2003. "Labor- And Capital-Augmenting Technical Change," Journal of the European Economic Association, MIT Press, vol. 1(1), pages 1-37, March.
    15. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    16. Hong Cheng & Ruixue Jia & Dandan Li & Hongbin Li, 2019. "The Rise of Robots in China," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 71-88, Spring.
    17. 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.
    18. Tomohara, Akinori & Takii, Sadayuki, 2011. "Does globalization benefit developing countries? Effects of FDI on local wages," Journal of Policy Modeling, Elsevier, vol. 33(3), pages 511-521, May.
    19. Shuai Guan & Jinquan Liu & Yongfu Liu & Mingze Du, 2022. "The Nonlinear Influence of Environmental Regulation on the Transformation and Upgrading of Industrial Structure," IJERPH, MDPI, vol. 19(14), pages 1-16, July.
    20. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    21. Dai, Yixin & Hu, Yuanhong & Tian, Chuanpeng & Jiang, Min, 2024. "China's biased technological progress, labor market allocation and the change of trade division structure," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1417-1430.
    22. Duncan K. Foley & Thomas R. Michl, 2001. "The Production Function and Productivity: Comment," Journal of Economic Perspectives, American Economic Association, vol. 15(3), pages 257-258, Summer.
    23. repec:nbr:nberch:14019 is not listed on IDEAS
    24. 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.
    25. Wemy, Edouard, 2021. "Capital-labor substitution elasticity: A simulated method of moments approach," Economic Modelling, Elsevier, vol. 97(C), pages 14-44.
    26. Ann Harrison, 2022. "Has Globalization Eroded Labor’s Share? Some Cross-Country Evidence," World Scientific Book Chapters, in: Globalization, Firms, and Workers, chapter 5, pages 89-135, World Scientific Publishing Co. Pte. Ltd..
    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. Li, Xiaofan & Wang, Qiaochu & Kong, Dongmin & Tao, Yunqing, 2025. "Intelligent manufacturing and corporate human capital upgrade in China," Journal of Asian Economics, Elsevier, vol. 97(C).

    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. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2019. "How can robots affect wage inequality?," Economic Modelling, Elsevier, vol. 81(C), pages 161-169.
    2. Gregory Casey, 2018. "Technology-Driven Unemployment," 2018 Meeting Papers 302, Society for Economic Dynamics.
    3. Cheng, Can & Luo, Jiayu & Zhu, Chun & Zhang, Shangfeng, 2024. "Artificial intelligence and the skill premium: A numerical analysis of theoretical models," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    4. Gregory Casey & Ryo Horii, 2019. "A Multi-factor Uzawa Growth Theorem and Endogenous Capital-Augmenting Technological Change," ISER Discussion Paper 1051, Institute of Social and Economic Research, The University of Osaka.
    5. 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).
    6. 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.
    7. 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.
    8. 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.
    9. David E. Bloom & Klaus Prettner & Jamel Saadaoui & Mario Veruete, 2023. "Artificial intelligence and the skill premium," Papers 2311.09255, arXiv.org.
    10. M. Battisti & M. Del Gatto & A. F. Gravina & C. F. Parmeter, 2021. "Robots versus labor skills: a complementarity/substitutability analysis," Working Paper CRENoS 202104, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    11. 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.
    12. Lihua Zhang & Tian Gan & Jiachen Fan, 2023. "Do industrial robots affect the labour market? Evidence from China," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 31(3), pages 787-817, July.
    13. Arntz, Melanie & Gregory, Terry & Zierahn-Weilage, Ulrich, 2019. "Digitalization and the Future of Work: Macroeconomic Consequences," IZA Discussion Papers 12428, Institute of Labor Economics (IZA).
    14. FU, Yunyun & SHEN, Yongchang & SONG, Malin & WANG, Weiyu, 2024. "Does artificial intelligence reduce corporate energy consumption? New evidence from China," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 548-561.
    15. Robert Stehrer, 2022. "The Impact of ICT and Intangible Capital Accumulation on Labour Demand Growth and Functional Income Shares," wiiw Working Papers 218, The Vienna Institute for International Economic Studies, wiiw.
    16. Wang, Linhui & Cao, Zhanglu & Dong, Zhiqing, 2023. "Are artificial intelligence dividends evenly distributed between profits and wages? Evidence from the private enterprise survey data in China," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 342-356.
    17. 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.
    18. Chen, Kaiming & Chen, Xiaoqian & Wang, Zhan-ao & Zvarych, Roman, 2024. "Does artificial intelligence promote common prosperity within enterprises? —Evidence from Chinese-listed companies in the service industry," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    19. Robert Z. Lawrence, 2015. "Recent Declines in Labor's Share in US Income: A Preliminary Neoclassical Account," Working Paper Series WP15-10, Peterson Institute for International Economics.
    20. Ke-Liang Wang & Ting-Ting Sun & Ru-Yu Xu, 2023. "The impact of artificial intelligence on total factor productivity: empirical evidence from China’s manufacturing enterprises," Economic Change and Restructuring, Springer, vol. 56(2), pages 1113-1146, April.

    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:eee:ecanpo:v:84:y:2024:i:c:p:42-56. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/economic-analysis-and-policy .

    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.