IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0280225.html
   My bibliography  Save this article

Digital economy development and the urban-rural income gap: Evidence from Chinese cities

Author

Listed:
  • Xiang Deng
  • Meng Guo
  • Yuyan Liu

Abstract

The growth of the digital economy has created new forms of inequality of opportunity. This paper studies whether the development of the digital economy expands the income gap between urban and rural areas from theoretical and empirical. The research based on the panel data of 202 cities from 2011 to 2019 in China shows that: (1) Although the digital economy can promote the improvement of both urban and rural absolute income levels, it has a greater positive impact on urban residents’ income levels than on rural residents’, resulting in a widening of the urban-rural income gap. (2) The analysis of the action mechanism reveals that employment in the information service industry and the depth of digital finance use are two crucial mechanisms for the digital economy to widen the income gap between urban and rural areas. (3) The spatial Durbin model(SDM) and the spatial error model(SEM) based on three spatial weight matrices show that the impact of the digital economy on the urban-rural income gap is also characterized by spatial spillover, and the development of the digital economy will also have a negative impact on the urban-rural income gap in neighboring regions as well. (4) The main conclusions still hold after the robustness of quasi-natural experiments based on the strategy of "Broadband China" and the selection of historical data as instrumental variables. This research is helpful to understand the effects, mechanisms and spatial characteristics of digital economy on urban-rural income gap.

Suggested Citation

  • Xiang Deng & Meng Guo & Yuyan Liu, 2023. "Digital economy development and the urban-rural income gap: Evidence from Chinese cities," PLOS ONE, Public Library of Science, vol. 18(2), pages 1-25, February.
  • Handle: RePEc:plo:pone00:0280225
    DOI: 10.1371/journal.pone.0280225
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0280225
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0280225&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0280225?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
    ---><---

    References listed on IDEAS

    as
    1. Shorrocks, A F, 1980. "The Class of Additively Decomposable Inequality Measures," Econometrica, Econometric Society, vol. 48(3), pages 613-625, April.
    2. Georg Graetz & Guy Michaels, 2017. "Is Modern Technology Responsible for Jobless Recoveries?," American Economic Review, American Economic Association, vol. 107(5), pages 168-173, May.
    3. Huisheng Yu & Jun Yang & Dongqi Sun & Tong Li & Yanjun Liu, 2022. "Spatial Responses of Ecosystem Service Value during the Development of Urban Agglomerations," Land, MDPI, vol. 11(2), pages 1-12, January.
    4. Dale W. Jorgenson, 1967. "Surplus Agricultural Labour And The Development Of A Dual Economy," Oxford Economic Papers, Oxford University Press, vol. 19(3), pages 288-312.
    5. 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.
    6. DeCanio, Stephen J., 2016. "Robots and humans – complements or substitutes?," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 280-291.
    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. 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).
    2. Daniele Angelini, 2023. "Aging Population and Technology Adoption," Working Paper Series of the Department of Economics, University of Konstanz 2023-01, Department of Economics, University of Konstanz.
    3. Hideki Nakamura, 2024. "Can displaced workers have a fresh start?," Metroeconomica, Wiley Blackwell, vol. 75(1), pages 83-106, February.
    4. Dai, Hangrui & Yang, Ronghai & Cao, Rongguang & Yin, Lei, 2024. "Does the application of industrial robots promote export green transformation? Evidence from Chinese manufacturing enterprises," International Review of Economics & Finance, Elsevier, vol. 96(PA).
    5. Liang, Peng & Liang, Lin & Tang, Xinhui, 2024. "The impact of digital-oriented mergers and acquisitions on enterprise labor demand," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    6. Du, Junhong & He, Jiajia & Yang, Jing & Chen, Xiaohong, 2024. "How industrial robots affect labor income share in task model: Evidence from Chinese A-share listed companies," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    7. Nakamura, Hideki, 2023. "Difficulties in finding middle-skilled jobs under increased automation," Macroeconomic Dynamics, Cambridge University Press, vol. 27(5), pages 1179-1201, July.
    8. Ghodsi, Mahdi & Stehrer, Robert & Barišić, Antea, 2024. "Assessing the impact of new technologies on wages and labour income shares," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    9. Lei Wang & Provash Sarker & Kausar Alam & Shahneoaj Sumon, 2021. "Artificial Intelligence and Economic Growth: A Theoretical Framework," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 68(4), pages 421-443, November.
    10. 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.
    11. Wang, Linhui & Wang, Hui & Cao, Zhanglu & He, Yongda & Dong, Zhiqing & Wang, Shixiang, 2022. "Can industrial intellectualization reduce carbon emissions? — Empirical evidence from the perspective of carbon total factor productivity in China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    12. Davide Dottori, 2021. "Robots and employment: evidence from Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 739-795, July.
    13. Azio Barani, 2021. "Innovazione tecnologica e lavoro: automazione, occupazione e impatti socio-economici," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 0(114), pages 51-79.
    14. Jurkat, Anne & Klump, Rainer & Schneider, Florian, 2023. "Robots and Wages: A Meta-Analysis," EconStor Preprints 274156, ZBW - Leibniz Information Centre for Economics.
    15. Cui, Huijie & Liang, Shangkun & Xu, Canyu & Junli, Yu, 2024. "Robots and analyst forecast precision: Evidence from Chinese manufacturing," International Review of Financial Analysis, Elsevier, vol. 94(C).
    16. Pablo Casas & José L. Torres, 2023. "Automation, automatic capital returns, and the functional income distribution," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 32(1), pages 113-135, January.
    17. Enzo Valentini & Fabiano Compagnucci & Mauro Gallegati & Andrea Gentili, 2023. "Robotization, employment, and income: regional asymmetries and long-run policies in the Euro area," Journal of Evolutionary Economics, Springer, vol. 33(3), pages 737-771, July.
    18. Stähler, Nikolai, 2021. "The Impact of Aging and Automation on the Macroeconomy and Inequality," Journal of Macroeconomics, Elsevier, vol. 67(C).
    19. Baek, Seungjin & Jeong, Deokjae, 2023. "Factors Influencing Labor Share: Automation, Task Innovation, and Elasticity of Substitution," MPRA Paper 118730, University Library of Munich, Germany.
    20. 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.

    More about this item

    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:plo:pone00:0280225. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.