IDEAS home Printed from https://ideas.repec.org/a/tcb/cebare/v22y2022i3p119-127.html
   My bibliography  Save this article

Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failures

Author

Listed:
  • Abdus Samad
  • Vaughn S. Armstrong

Abstract

This paper examines prediction of U.S. bank failure with a probit model that uses bias-corrected technical efficiency estimated using bootstrap data envelopment analysis as the measure of management quality. The model is tested on a sample of failed and non-failed banks during the sub-prime mortgage meltdown, 2008–2009. Results demonstrate this measure of management efficiency, together with other CAMEL factors (i.e., capital adequacy, asset quality, earnings quality, and liquidity), is significant for predicting bank failure. This measure of managerial quality allows more accurate prediction of failure than other measures. The model successfully predicts bank failure one and two years prior to failure. ######### keywords

Suggested Citation

  • Abdus Samad & Vaughn S. Armstrong, 2022. "Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failures," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 22(3), pages 119-127.
    • Handle: RePEc:tcb:cebare:v:22:y:2022:i:3:p:119-127
    as

    Download full text from publisher

    File URL: https://www.sciencedirect.com/science/article/pii/S1303070122000208
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Wang, Haibo & Sua, Lutfu & Dolar, Burak, 2023. "CAMELs-DEA in Assessing the Role of Major Factors in Achieving Higher Efficiency Levels: Evidence from Turkish Banks," SocArXiv qx59v, Center for Open Science.

    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:tcb:cebare:v:22:y:2022:i:3:p:119-127. 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: the person in charge or the person in charge or the person in charge or the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/tcmgvtr.html .

    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.