IDEAS home Printed from https://ideas.repec.org/a/kap/ecopln/v57y2024i4d10.1007_s10644-024-09729-3.html
   My bibliography  Save this article

Big data and inter-firm wage disparities: theory and evidence from China

Author

Listed:
  • Han Bu

    (Southwest University)

  • Zhou Xun

    (Nanjing University of Finance and Economics)

  • Sha Cai

    (University of Southampton)

Abstract

While Big Data is driving high-quality firm development, it will also have a new impact on wage differences among firms, which is a less discussed topic in the literature. A theoretical model indicates that Big Data as an element-enhancing factor could influence inter-firm wage disparities by altering differences in productivity and the labor skill structure across firms. Taking data from Chinese A-share listed companies spanning from 2008 to 2022 and leveraging the establishment of National Comprehensive Big Data Pilot Zones (NCBDPZ) in China as an exogenous event, we employ a staggered DID model to empirically investigate the relationship between Big Data and inter-firm wage disparities. Our findings reveal that Big Data significantly reduces inter-firm wage disparities within the city. This conclusion remains robust after undergoing rigorous tests like parallel trend analysis and placebo tests. Mechanism analysis indicates that Big Data can narrow the inter-firm wage disparities by mitigating labor productivity and labor skill structure disparities among firms. Furthermore, our further analysis demonstrates that the reducing effect of Big Data on inter-firm wage disparities is primarily observed in the Secondary sector, with the most pronounced impact being within western regions in China. In addition, it is noteworthy that Big Data primarily enhances intra-distribution of labor income by alleviating wage disparities between firms rather than within. This study contributes to understanding how data elements can reshape income distribution structures, offering valuable insights for government entities seeking to strengthen the role of Big Data in reducing income disparities.

Suggested Citation

  • Han Bu & Zhou Xun & Sha Cai, 2024. "Big data and inter-firm wage disparities: theory and evidence from China," Economic Change and Restructuring, Springer, vol. 57(4), pages 1-36, August.
  • Handle: RePEc:kap:ecopln:v:57:y:2024:i:4:d:10.1007_s10644-024-09729-3
    DOI: 10.1007/s10644-024-09729-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10644-024-09729-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10644-024-09729-3?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. David Card & Ana Rute Cardoso & Joerg Heining & Patrick Kline, 2018. "Firms and Labor Market Inequality: Evidence and Some Theory," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 13-70.
    2. David Card & Jörg Heining & Patrick Kline, 2013. "Workplace Heterogeneity and the Rise of West German Wage Inequality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(3), pages 967-1015.
    3. Eric A. Verhoogen, 2008. "Trade, Quality Upgrading, and Wage Inequality in the Mexican Manufacturing Sector," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(2), pages 489-530.
    4. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    5. 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.
    6. Philippe Aghion & Antonin Bergeaud & Timo Boppart & Peter J Klenow & Huiyu Li, 2023. "A Theory of Falling Growth and Rising Rents," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(6), pages 2675-2702.
    7. Deborah Goldschmidt & Johannes F. Schmieder, 2017. "The Rise of Domestic Outsourcing and the Evolution of the German Wage Structure," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(3), pages 1165-1217.
    8. David Autor & David Dorn & Lawrence F Katz & Christina Patterson & John Van Reenen, 2020. "The Fall of the Labor Share and the Rise of Superstar Firms [“Automation and New Tasks: How Technology Displaces and Reinstates Labor”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 645-709.
    9. Stefan Bender & Nicholas Bloom & David Card & John Van Reenen & Stefanie Wolter, 2018. "Management Practices, Workforce Selection, and Productivity," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 371-409.
    10. Gilbert Cette & Sandra Nevoux & Loriane Py, 2022. "The impact of ICTs and digitalization on productivity and labor share: evidence from French firms," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 31(8), pages 669-692, November.
    11. Clifford Lynch, 2008. "How do your data grow?," Nature, Nature, vol. 455(7209), pages 28-29, September.
    12. Elhanan Helpman & Oleg Itskhoki & Stephen Redding, 2010. "Inequality and Unemployment in a Global Economy," Econometrica, Econometric Society, vol. 78(4), pages 1239-1283, July.
    13. Behl, Abhishek & Gaur, Jighyasu & Pereira, Vijay & Yadav, Rambalak & Laker, Benjamin, 2022. "Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19 – A multi-theoretical approach," Journal of Business Research, Elsevier, vol. 148(C), pages 378-389.
    14. Jian Jia & Ginger Zhe Jin & Liad Wagman, 2021. "The Short-Run Effects of the General Data Protection Regulation on Technology Venture Investment," Marketing Science, INFORMS, vol. 40(4), pages 661-684, July.
    15. Anping Chen & Tianshi Dai & Mark D. Partridge, 2021. "Agglomeration and firm wage inequality: Evidence from China," Journal of Regional Science, Wiley Blackwell, vol. 61(2), pages 352-386, March.
    16. Zi Hui Yin & Chang Hwan Choi, 2023. "Does digitalization contribute to lesser income inequality? Evidence from G20 countries," Information Technology for Development, Taylor & Francis Journals, vol. 29(1), pages 61-82, January.
    17. Chiara Criscuolo & Alexander Hijzen & Cyrille Schwellnus & Erling Barth & Wen-Hao Chen & Richard Fabling & Priscilla Fialho & Balazs Stadler & Richard Upward & Wouter Zwysen & Katarzyna Grabska-Romago, 2020. "Workforce composition, productivity and pay: the role of firms in wage inequality," OECD Economics Department Working Papers 1603, OECD Publishing.
    18. Erik Brynjolfsson & Kristina McElheran, 2016. "The Rapid Adoption of Data-Driven Decision-Making," American Economic Review, American Economic Association, vol. 106(5), pages 133-139, May.
    19. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    20. Cortes, Matias & Lerche, Adrian & Schönberg, Uta & Tschopp, Jeanne, 2023. "Technological Change, Firm Heterogeneity and Wage Inequality," IZA Discussion Papers 16070, Institute of Labor Economics (IZA).
    21. 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.
    22. Michael Gibbs & Sergei Bazylik, 2022. "How is new technology changing job design?," IZA World of Labor, Institute of Labor Economics (IZA), pages 344-344, August.
    23. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    24. Charles I. Jones & Christopher Tonetti, 2020. "Nonrivalry and the Economics of Data," American Economic Review, American Economic Association, vol. 110(9), pages 2819-2858, September.
    25. Elisabetta Raguseo & Claudio Vitari, 2018. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," International Journal of Production Research, Taylor & Francis Journals, vol. 56(15), pages 5206-5221, August.
    26. Christian Dustmann & Johannes Ludsteck & Uta Schönberg, 2009. "Revisiting the German Wage Structure," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(2), pages 843-881.
    27. Patrick Kline & Neviana Petkova & Heidi Williams & Owen Zidar, 2019. "Who Profits from Patents? Rent-Sharing at Innovative Firms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(3), pages 1343-1404.
    28. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    29. Martin Biewen & Matthias Seckler, 2019. "Unions, Internationalization, Tasks, Firms, and Worker Characteristics: A Detailed Decomposition Analysis of Rising Wage Inequality in Germany," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(4), pages 461-498, December.
    30. Sanghoon Ahn, 2001. "Firm Dynamics and Productivity Growth: A Review of Micro Evidence from OECD Countries," OECD Economics Department Working Papers 297, OECD Publishing.
    31. Clemens Ohlert, 2016. "Establishment heterogeneity, rent sharing and the rise of wage inequality in Germany," International Journal of Manpower, Emerald Group Publishing Limited, vol. 37(2), pages 210-228, May.
    32. Mikalef, Patrick & Boura, Maria & Lekakos, George & Krogstie, John, 2019. "Big data analytics and firm performance: Findings from a mixed-method approach," Journal of Business Research, Elsevier, vol. 98(C), pages 261-276.
    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. Berlingieri, Giuseppe & Blanchenay, Patrick & Criscuolo, Chiara, 2024. "The great divergence(s)," Research Policy, Elsevier, vol. 53(3).
    2. Cortes, Matias & Lerche, Adrian & Schönberg, Uta & Tschopp, Jeanne, 2023. "Technological Change, Firm Heterogeneity and Wage Inequality," IZA Discussion Papers 16070, Institute of Labor Economics (IZA).
    3. Daniel Baumgarten & Gabriel Felbermayr & Sybille Lehwald, 2020. "Dissecting Between‐Plant and Within‐Plant Wage Dispersion: Evidence from Germany," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 59(1), pages 85-122, January.
    4. Maarten Goos & Melanie Arntz & Ulrich Zierahn & Terry Gregory & Stephanie Carretero Gomez & Ignacio Gonzalez Vazquez & Koen Jonkers, 2019. "The Impact of Technological Innovation on the Future of Work," JRC Working Papers on Labour, Education and Technology 2019-03, Joint Research Centre.
    5. Benedikt Schröpf, 2023. "The dynamics of wage dispersion between firms: the role of firm entry and exit," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-29, December.
    6. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    7. Bergeaud, Antonin & Mazet-Sonilhac, Clément & Malgouyres, Clément & Signorelli, Sara, 2021. "Technological Change and Domestic Outsourcing," IZA Discussion Papers 14603, Institute of Labor Economics (IZA).
    8. Diego Daruich & Sabrina Di Addario & Raffaele Saggio, 2023. "The Effects of Partial Employment Protection Reforms: Evidence from Italy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(6), pages 2880-2942.
    9. Muendler, Marc-Andreas, 2017. "Trade, technology, and prosperity: An account of evidence from a labor-market perspective," WTO Staff Working Papers ERSD-2017-15, World Trade Organization (WTO), Economic Research and Statistics Division.
    10. Winkler, Erwin, 2020. "Diverging paths: Labor reallocation, sorting, and wage inequality," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224535, Verein für Socialpolitik / German Economic Association.
    11. Mertens, Matthias, 2023. "Labor Market Power and Between-Firm Wage (In)Equality," International Journal of Industrial Organization, Elsevier, vol. 91(C).
    12. Arntz, Melanie & Genz, Sabrina & Gregory, Terry & Lehmer, Florian & Zierahn-Weilage, Ulrich, 2024. "De-Routinization in the Fourth Industrial Revolution - Firm-Level Evidence," IZA Discussion Papers 16740, Institute of Labor Economics (IZA).
    13. Mary O’Mahony & Michela Vecchi & Francesco Venturini, 2021. "Capital Heterogeneity and the Decline of the Labour Share," Economica, London School of Economics and Political Science, vol. 88(350), pages 271-296, April.
    14. Feld, Lars P. & Schmidt, Christoph M. & Schnabel, Isabel & Truger, Achim & Wieland, Volker, 2019. "Den Strukturwandel meistern. Jahresgutachten 2019/20 [Dealing with Structural Change. Annual Report 2019/20]," Annual Economic Reports / Jahresgutachten, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung, volume 127, number 201920.
    15. Bas Scheer & Wiljan van den Berge & Maarten Goos & Alan Manning & Anna Salomons, 2022. "Alternative Work Arrangements and Worker Outcomes: Evidence from Payrolling," CPB Discussion Paper 435, CPB Netherlands Bureau for Economic Policy Analysis.
    16. Federico Huneeus & Kory Kroft & Kevin Lim, 2021. "Earnings Inequality in Production Networks," NBER Working Papers 28424, National Bureau of Economic Research, Inc.
    17. Benjamin Faber & Thibault Fally, 2022. "Firm Heterogeneity in Consumption Baskets: Evidence from Home and Store Scanner Data [Measuring Trends in Leisure: The Allocation of Time over Five Decades]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(3), pages 1420-1459.
    18. Christopher Cornwell & Ian M. Schmutte & Daniela Scur, 2021. "Building a Productive Workforce: The Role of Structured Management Practices," Management Science, INFORMS, vol. 67(12), pages 7308-7321, December.
    19. Gregor Hesse, 2015. "Inequality in a global economy: evidence from Germany," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 151(4), pages 803-820, November.
    20. von Maydell, Richard, 2024. "Artificial Intelligence and its Effect on Competition and Factor Income Shares," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277654, Verein für Socialpolitik / German Economic Association, revised 2024.

    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:kap:ecopln:v:57:y:2024:i:4:d:10.1007_s10644-024-09729-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.