IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v93y2026ics1544612325026807.html

Intelligent revolution of educational resources: AI-driven reallocation effects and economic consequences

Author

Listed:
  • Yang, Bo
  • Hu, Hao
  • Li, Yixuan

Abstract

Because artificial intelligence (AI) is deeply integrated into urban governance systems, educational resource allocation is undergoing profound structural transformation. Using panel data from Chinese prefecture-level cities spanning 2000–2023, this study systematically and empirically explores the multidimensional impacts, inherent mechanisms, and economic consequences of AI development on educational resource allocation. Notably, AI development has a significant structural effect on educational resource allocation, substantially increasing the scale of urban fiscal expenditure on education and the number of full-time teachers and promoting rational reductions in the number of schools, which drives the education system toward centralization and digital platforming. This is primarily achieved by enhancing local fiscal coordination capacity and attracting highly educated populations. Furthermore, this AI-driven restructuring of educational resources increases urban per capita GDP. This study underscores the pivotal role of AI in reshaping public resource allocation. Our findings provide significant theoretical support and practical references for resource-constrained regions to develop accurate, AI-enabled education policies, address imbalanced educational development, and promote educational equity and coordinated, sustainable regional development.

Suggested Citation

  • Yang, Bo & Hu, Hao & Li, Yixuan, 2026. "Intelligent revolution of educational resources: AI-driven reallocation effects and economic consequences," Finance Research Letters, Elsevier, vol. 93(C).
  • Handle: RePEc:eee:finlet:v:93:y:2026:i:c:s1544612325026807
    DOI: 10.1016/j.frl.2025.109431
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612325026807
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2025.109431?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.

    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:eee:finlet:v:93:y:2026:i:c:s1544612325026807. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.