IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6239-689-0_8.html

Who is Paying for Healthcare and School Enrollment? —A Study Based on County-Level Panel Data in China from 2000 to 2023

In: Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026)

Author

Listed:
  • Zhe Li

    (City University of Macau, Faculty of Finance)

  • Di Hu

    (City University of Macau, Faculty of Finance)

  • Wushen Huang

    (City University of Macau, Faculty of Finance)

  • Ziyun Wang

    (Hainan Vocational University of Science and Technology, School of Accounting)

Abstract

This paper proposes a simple unit fiscal burden (UFB) framework to track sector-specific cost dynamics in local public services. Using county-level panel data in China from 2000–2023, we construct UFB measures for healthcare and primary education as sectoral public expenditure per unit of service capacity (hospital beds and primary-school enrollment), expressed in logs. We document a persistent divergence in which expenditure grows much faster than capacity, implying sustained increases in unit burdens. Fixed-effects regressions show that both fiscal capacity (per-capita budget revenue) and fiscal pressure (the expenditure-to-revenue ratio) are positively and significantly associated with UFB in both sectors. Moreover, the association between fiscal capacity and UFB is stronger in high-pressure counties, consistent with tighter budget constraints amplifying cost intensity rather than facilitating proportional capacity expansion. The proposed indicators provide a practical tool for monitoring fiscal risk and service-cost inflation at the local level.

Suggested Citation

  • Zhe Li & Di Hu & Wushen Huang & Ziyun Wang, 2026. "Who is Paying for Healthcare and School Enrollment? —A Study Based on County-Level Panel Data in China from 2000 to 2023," Advances in Economics, Business and Management Research, in: Ljiljana Trajkovic & José Alfredo F. Costa & Zaher Al Aghbari & Nor Azman Ismail & Dariusz Jacek Jak (ed.), Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026), pages 70-82, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6239-689-0_8
    DOI: 10.2991/978-94-6239-689-0_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:advbcp:978-94-6239-689-0_8. 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: 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.