IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v90y2025ics0927538x25000289.html
   My bibliography  Save this article

How does artificial intelligence shock affect labor income distribution? Evidence from China

Author

Listed:
  • Fan, Xiamin
  • Wu, Yuhui
  • Zhou, Yucheng
  • Wu, Shinong

Abstract

Based on the neoclassical growth model and labor-management negotiation framework, we theoretically investigate the impact and mechanism of artificial intelligence (AI) shocks on the labor income share of firms. We then take China's “New-generation Artificial Intelligence Pilot Zone Policy” (AI pilot zone policy) as an exogenous shock and analyze micro-level corporate data. Employing a staggered difference-in-differences model, we find that the AI pilot zone policy significantly increases the labor income share in firms, primarily through the skill demand and skill premium effects. Our results withstand various robustness tests. Furthermore, we observe that the AI pilot zone policy has a more pronounced impact on the labor income share in firms characterized by high labor rigidity, low wage premiums, non-labor-intensive industries, and high-tech sectors.

Suggested Citation

  • Fan, Xiamin & Wu, Yuhui & Zhou, Yucheng & Wu, Shinong, 2025. "How does artificial intelligence shock affect labor income distribution? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:pacfin:v:90:y:2025:i:c:s0927538x25000289
    DOI: 10.1016/j.pacfin.2025.102691
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X25000289
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.pacfin.2025.102691?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Jack Favilukis & Xiaoji Lin & Xiaofei Zhao, 2020. "The Elephant in the Room: The Impact of Labor Obligations on Credit Markets," American Economic Review, American Economic Association, vol. 110(6), pages 1673-1712, June.
    2. David Autor & Anna Salomons, 2018. "Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share," NBER Working Papers 24871, National Bureau of Economic Research, Inc.
    3. Anders Akerman & Ingvil Gaarder & Magne Mogstad, 2015. "The Skill Complementarity of Broadband Internet," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1781-1824.
    4. Gene M. Grossman & Elhanan Helpman & Ezra Oberfield & Thomas Sampson, 2017. "Balanced Growth Despite Uzawa," American Economic Review, American Economic Association, vol. 107(4), pages 1293-1312, April.
    5. 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.
    6. Anastassia Fedyk & James Hodson & Natalya Khimich & Tatiana Fedyk, 2022. "Is artificial intelligence improving the audit process?," Review of Accounting Studies, Springer, vol. 27(3), pages 938-985, September.
    7. Wolfgang Dauth & Sebastian Findeisen & Jens Suedekum & Nicole Woessner, 2021. "The Adjustment of Labor Markets to Robots [“Skills, Tasks and Technologies: Implications for Employment and Earnings]," Journal of the European Economic Association, European Economic Association, vol. 19(6), pages 3104-3153.
    8. Ezra Oberfield & Devesh Raval, 2021. "Micro Data and Macro Technology," Econometrica, Econometric Society, vol. 89(2), pages 703-732, March.
    9. 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.
    10. David Rezza Baqaee, 2018. "Cascading Failures in Production Networks," Econometrica, Econometric Society, vol. 86(5), pages 1819-1838, September.
    11. Xiao, Gang & Shen, Sichen, 2022. "To pollute or not to pollute: Political connections and corporate environmental performance," Journal of Corporate Finance, Elsevier, vol. 74(C).
    12. Paul Beaudry & Mark Doms & Ethan Lewis, 2010. "Should the Personal Computer Be Considered a Technological Revolution? Evidence from U.S. Metropolitan Areas," Journal of Political Economy, University of Chicago Press, vol. 118(5), pages 988-1036.
    13. 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.
    14. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    15. H. Uzawa, 1961. "Neutral Inventions and the Stability of Growth Equilibrium," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 28(2), pages 117-124.
    16. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2018. "Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 23-57, National Bureau of Economic Research, Inc.
    17. Wei, Xiahai & Jiang, Feng & Su, Yaqin, 2024. "More green, less labor gains? Green factory and labor income share in China," Energy Economics, Elsevier, vol. 133(C).
    18. Bentolila Samuel & Saint-Paul Gilles, 2003. "Explaining Movements in the Labor Share," The B.E. Journal of Macroeconomics, De Gruyter, vol. 3(1), pages 1-33, October.
    19. Rainer Klump & Peter McAdam & Alpo Willman, 2012. "The Normalized Ces Production Function: Theory And Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 26(5), pages 769-799, December.
    20. Daron Acemoglu, 2003. "Labor- And Capital-Augmenting Technical Change," Journal of the European Economic Association, MIT Press, vol. 1(1), pages 1-37, March.
    21. DeCanio, Stephen J., 2016. "Robots and humans – complements or substitutes?," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 280-291.
    22. Johan Hombert & Antoinette Schoar & David Sraer & David Thesmar, 2020. "Can Unemployment Insurance Spur Entrepreneurial Activity? Evidence from France," Journal of Finance, American Finance Association, vol. 75(3), pages 1247-1285, June.
    23. 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.
    24. 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.
    25. Daron Acemoglu & Pascual Restrepo, 2022. "Tasks, Automation, and the Rise in U.S. Wage Inequality," Econometrica, Econometric Society, vol. 90(5), pages 1973-2016, September.
    26. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    27. Luo, Sumei & Sun, Yongkun & Zhou, Rui, 2022. "Can fintech innovation promote household consumption? Evidence from China family panel studies," International Review of Financial Analysis, Elsevier, vol. 82(C).
    28. Doruk Cengiz & Arindrajit Dube & Attila Lindner & Ben Zipperer, 2019. "The Effect of Minimum Wages on Low-Wage Jobs," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(3), pages 1405-1454.
    29. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    30. Li, Chengming & Huo, Peng & Wang, Zeyu & Zhang, Weiguang & Liang, Feiyan & Mardani, Abbas, 2023. "Digitalization generates equality? Enterprises’ digital transformation, financing constraints, and labor share in China," Journal of Business Research, Elsevier, vol. 163(C).
    31. Zhu, Wenpeng, 2023. "Digital financial inclusion and the share of labor income: Firm-level evidence," Finance Research Letters, Elsevier, vol. 56(C).
    32. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    33. 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. Deng, Liuchun & Müller, Steffen & Plümpe, Verena & Stegmaier, Jens, 2024. "Robots, occupations, and worker age: A production-unit analysis of employment," European Economic Review, Elsevier, vol. 170(C).
    2. David Autor & Caroline Chin & Anna Salomons & Bryan Seegmiller, 2024. "New Frontiers: The Origins and Content of New Work, 1940–2018," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(3), pages 1399-1465.
    3. 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.
    4. Qian, Cheng & Zhu, Chun & Huang, Duen-Huang & Zhang, Shangfeng, 2023. "Examining the influence mechanism of artificial intelligence development on labor income share through numerical simulations," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    5. Camiña, Ester & Díaz-Chao, Ángel & Torrent-Sellens, Joan, 2020. "Automation technologies: Long-term effects for Spanish industrial firms," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    6. 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.
    7. Baek, Seungjin & Jeong, Deokjae, 2023. "Factors Influencing Labor Share: Automation, Task Innovation, and Elasticity of Substitution," MPRA Paper 118730, University Library of Munich, Germany.
    8. 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).
    9. Gao, Jie & Li, Zhizhuo & Nguyen, Thithuha & Zhang, Wentao, 2025. "Digital transformation and enterprise employment," International Review of Economics & Finance, Elsevier, vol. 99(C).
    10. Zhou, Yuwen & Shi, Xin, 2025. "How does digital technology adoption affect corporate employment? Evidence from China," Economic Modelling, Elsevier, vol. 147(C).
    11. repec:ces:ceswps:_10955 is not listed on IDEAS
    12. Guimarães, Luís & Mazeda Gil, Pedro, 2022. "Explaining the Labor Share: Automation Vs Labor Market Institutions," Labour Economics, Elsevier, vol. 75(C).
    13. Wu, Yifan & Yuan, Yiming & Song, Xueyin, 2025. "The impact of AI adoption on R&D productivity: Evidence from Chinese pharmaceutical manufacturing industry," Journal of Asian Economics, Elsevier, vol. 97(C).
    14. Niu, Meng & Wang, Zhenguo & Zhang, Yabin, 2022. "How information and communication technology drives (routine and non-routine) jobs: Structural path and decomposition analysis for China," Telecommunications Policy, Elsevier, vol. 46(1).
    15. 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.
    16. 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.
    17. Jacobs, Arthur, 2023. "Capital-augmenting technical change in the context of untapped automation opportunities," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 155-166.
    18. You, Jing & Xu, Xiangyu & Liao, Deng & Lin, Chen, 2024. "International comparison of the impact of digital transformation on employment," Journal of Asian Economics, Elsevier, vol. 95(C).
    19. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    20. Li, Xin & Liu, Zhaoda & Ye, Yongwei, 2024. "Public data and corporate employment: Evidence from the launch of Chinese public data platform," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 124-144.
    21. David Marguerit, 2025. "Augmenting or Automating Labor? The Effect of AI Development on New Work, Employment, and Wages," Papers 2503.19159, arXiv.org.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    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:eee:pacfin:v:90:y:2025:i:c:s0927538x25000289. 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.elsevier.com/locate/pacfin .

    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.