IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v96y2024ipas1057521924005362.html
   My bibliography  Save this article

Green credit efficiency of commercial banks in China: Evidence from a multi-period leader-follower model with preference

Author

Listed:
  • Li, Jingyu
  • Guo, Xiangyuan
  • Xie, Qiwei
  • Sun, Xiaolei

Abstract

The efficiency of green credit in commercial banks is important for promoting green economic development. But seldom studies have investigated the efficiency evaluation of banking green credit activities. To fill this gap, this paper proposes a model for assessing the efficiency of green credit and further investigates the factors that potentially affect the efficiencies. The evaluation model for green credit efficiency is built through a multi-period leader-follower framework by innovatively considering green credit as an inherent input-output indicator with preference. The results demonstrate that the green credit efficiency of the Chinese commercial banks in the profit earning stage generally surpasses that in the deposit conversion stage. Throughout the multi-period analysis, the majority of banks, especially those that are state-owned, have improved their deposit conversion efficiency from 2017 to 2021. The efficiency in the profit earning stage for all banks significantly declined due to the impact of COVID-19. Bank size, asset quality, and macroeconomic conditions have significant influences on green credit efficiency. However, their influences vary heterogeneously across different stages and types of banks.

Suggested Citation

  • Li, Jingyu & Guo, Xiangyuan & Xie, Qiwei & Sun, Xiaolei, 2024. "Green credit efficiency of commercial banks in China: Evidence from a multi-period leader-follower model with preference," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    • Handle: RePEc:eee:finana:v:96:y:2024:i:pa:s1057521924005362
    DOI: 10.1016/j.irfa.2024.103604
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521924005362
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2024.103604?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.

    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:finana:v:96:y:2024:i:pa:s1057521924005362. 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/620166 .

    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.