IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v29y2022i15p1365-1368.html
   My bibliography  Save this article

Corporate financial distress prediction based on controlling shareholder’s equity pledge

Author

Listed:
  • Zhitao Wang
  • Qiuyan Wang
  • Zi Nie
  • Bingcheng Li

Abstract

In the past literature, the prediction model of financial distress mainly used the information of corporate finance and corporate governance, and less considered the predictive effect of controlling shareholder information. Based on the sample of A-share listed companies in China from 2014 to 2019, this paper empirically investigates the incremental effect of controlling shareholder’s equity pledge on improving the accuracy of financial distress prediction. It is found that the information of controlling shareholder’s equity pledge can significantly improve the accuracy of financial distress prediction. After changing the definition of the explained variable and the data source, the conclusion remains robust. This paper verifies the role of controlling shareholder’s equity pledge in predicting financial distress, extends the selection of financial distress prediction model variables to the controlling shareholder level, and enriches the research on the economic consequences of equity pledge.

Suggested Citation

  • Zhitao Wang & Qiuyan Wang & Zi Nie & Bingcheng Li, 2022. "Corporate financial distress prediction based on controlling shareholder’s equity pledge," Applied Economics Letters, Taylor & Francis Journals, vol. 29(15), pages 1365-1368, September.
  • Handle: RePEc:taf:apeclt:v:29:y:2022:i:15:p:1365-1368
    DOI: 10.1080/13504851.2021.1931656
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2021.1931656
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13504851.2021.1931656?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 search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Soumya Ranjan SETHI & Dushyant Ashok MAHADIK, 2024. "Spotting Trouble Before It Starts: Has Financial Distress Prediction Evolved During 1985–2022," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 24(1), pages 181-206.
    2. Soumya Ranjan Sethi & Dushyant Ashok Mahadik & Rajkiran V. Bilolikar, 2024. "Exploring Trends and Advancements in Financial Distress Prediction Research: A Bibliometric Study," International Journal of Economics and Financial Issues, Econjournals, vol. 14(1), pages 164-179, January.

    More about this item

    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:taf:apeclt:v:29:y:2022:i:15:p:1365-1368. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.