IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v18y2026i7p3421-d1911686.html

Digital Economy, Factor Allocation and Urban–Rural Income Disparity: Insights from Prefecture-Level Data in China

Author

Listed:
  • Ran Wu

    (School of Administration, Northeastern University, Shenyang 110167, China
    School of Economics, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China)

  • Jichun Wang

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Xiaolei Wang

    (Business School, Harbin Institute of Technology, Harbin 150006, China)

Abstract

The rapid expansion of digitalization is reshaping factor mobility and income distribution between urban and rural areas, with important implications for inclusive and sustainable development. Using panel data for 277 prefecture-level cities in China from 2012 to 2022, this study examines how DE affects urban–rural income disparity from the perspectives of nonlinear effects, factor allocation, and spatial interdependence. Compared with existing studies based mainly on provincial data, this paper provides a more fine-grained analysis at the prefecture level and combines mediation, double-threshold, and spatial analysis within a unified framework. The results show that DE has a significant U-shaped effect on urban–rural income disparity, suggesting that digital development may initially narrow the gap but widen it after a certain stage. Urban–rural factor allocation acts as an important transmission channel, and its role exhibits a double-threshold characteristic. The effect of DE also varies across urban agglomeration types and stages of urbanization, with stronger impacts in more developed and urbanized regions. In addition, the direct effect of DE follows a U-shaped pattern, whereas its spatial spillover effect shows an inverted U-shape. These findings indicate that digitalization is not automatically equalizing and that its distributional consequences depend on factor allocation conditions, regional development stages, and spatial linkages. The study provides evidence for policies aimed at reducing urban–rural inequality and promoting more balanced and sustainable development.

Suggested Citation

  • Ran Wu & Jichun Wang & Xiaolei Wang, 2026. "Digital Economy, Factor Allocation and Urban–Rural Income Disparity: Insights from Prefecture-Level Data in China," Sustainability, MDPI, vol. 18(7), pages 1-22, April.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:7:p:3421-:d:1911686
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/18/7/3421/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/18/7/3421/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:18:y:2026:i:7:p:3421-:d:1911686. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.