IDEAS home Printed from https://ideas.repec.org/a/mes/emfitr/v59y2023i12p3798-3812.html
   My bibliography  Save this article

Does Credit Rating Provide Incremental Predictive Power on a Firm’s Future Financial Distress? Evidence from China

Author

Listed:
  • Lina Yan
  • Yao Hu
  • Minghuan Li
  • Kam C. Chan

Abstract

We examine the incremental predictive power of credit rating on a firm’s future financial distress using a sample of Chinese credit ratings from 2008 to 2019. Our findings suggest that such credit ratings, especially those using investor-pay mode, improve the incremental predictive power of firms’ future financial distress. Specifically, a one notch rating level increase of issuer-pay (investor-pay) credit rating translates into 1.69% (10.24%) lower probability of financial distress. The findings are robust to using a propensity score matching sample and an alternative metric for financial distress. Additional analysis suggests that the incremental predictive power of credit rating on financial distress is more salient for subsamples of credit ratings 1) issued by credit rating agencies (CRAs) with large market shares, 2) when a CRA has a low likelihood of collusion with a firm, or 3) when a firm receives both investor-pay and issuer-pay credit rating.

Suggested Citation

  • Lina Yan & Yao Hu & Minghuan Li & Kam C. Chan, 2023. "Does Credit Rating Provide Incremental Predictive Power on a Firm’s Future Financial Distress? Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 59(12), pages 3798-3812, September.
  • Handle: RePEc:mes:emfitr:v:59:y:2023:i:12:p:3798-3812
    DOI: 10.1080/1540496X.2023.2226325
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1540496X.2023.2226325
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/1540496X.2023.2226325?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.

    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:mes:emfitr:v:59:y:2023:i:12:p:3798-3812. 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/MREE20 .

    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.