IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v102y2025ics105905602500471x.html
   My bibliography  Save this article

Short selling and enterprise digital Transformation-A quasi-natural experiment based on financing and funding in China

Author

Listed:
  • Zhang, Haomin
  • Song, Jing
  • Song, Yu
  • Mai, Haixia

Abstract

This paper investigates the impact of short selling on the enterprise digital transformation in China's capital market. Our analysis of A-share listed firms (2007–2023) finds that short selling exerts a significant positive impact on enterprise digital transformation. The robustness of this association is substantiated through a difference-in-differences (DID) estimation strategy, demonstrating a statistically significant increase in the treatment effect coefficient (e.g., β = 0.114 VS β = 0.066, p < 0.01). We further observe two moderating effects on the relationship between short selling and enterprise digital transformation: absorptive capacity (β = 0.749, p < 0.01) and management equity incentives (β = 0.413, p < 0.01). These findings withstand multiple robustness tests, including alternative model specifications, variable measurements, and sample periods. We further find that short selling introduction positively relates to higher TobinQ values (β = 0.058, p < 0.01), with enterprise digital transformation mediating this effect as demonstrated through structural equation modeling.

Suggested Citation

  • Zhang, Haomin & Song, Jing & Song, Yu & Mai, Haixia, 2025. "Short selling and enterprise digital Transformation-A quasi-natural experiment based on financing and funding in China," International Review of Economics & Finance, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:reveco:v:102:y:2025:i:c:s105905602500471x
    DOI: 10.1016/j.iref.2025.104308
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S105905602500471X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2025.104308?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:102:y:2025:i:c:s105905602500471x. 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.