IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v106y2026ics1059056025010147.html

Digital rural development and agricultural economic resilience

Author

Listed:
  • Li, Zhengdao

Abstract

This research investigates how digital rural construction influences agricultural economic resilience within China, utilizing a comprehensive panel dataset comprising 31 provinces from 2012 to 2023. Grounded in resilience theory and infrastructure-led development frameworks, the analysis applies a two-way fixed effects model alongside instrumental variable estimation, propensity score matching, and Heckman selection models to ensure robust empirical validity. The results consistently indicate that digital rural construction exerts a significant and positive effect on agricultural economic resilience. Mechanism analysis identifies three distinct transmission pathways: digital infrastructure, agricultural industrial agglomeration, and agricultural technological innovation. Among these, digital infrastructure and industrial agglomeration function as primary mediators, while technological innovation plays a partial but significant role. Furthermore, heterogeneity analysis reveals that the positive impact of digital construction is most effective in regions characterized by high innovation capabilities and greater openness to external markets. These findings provide empirical evidence that digital transformation strengthens rural adaptive capacity by facilitating institutional modernization and industrial coordination. The study concludes with policy recommendations for optimizing rural revitalization strategies, emphasizing the need to align digital investment with regional innovation and market integration efforts.

Suggested Citation

  • Li, Zhengdao, 2026. "Digital rural development and agricultural economic resilience," International Review of Economics & Finance, Elsevier, vol. 106(C).
  • Handle: RePEc:eee:reveco:v:106:y:2026:i:c:s1059056025010147
    DOI: 10.1016/j.iref.2025.104851
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056025010147
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2025.104851?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:reveco:v:106:y:2026:i:c:s1059056025010147. 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/inca/620165 .

    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.