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

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...

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Bibliographic Details
Main Authors: Abdus Samad, Vaughn S. Armstrong
Format: Article
Language:English
Published: Elsevier 2022-09-01
Series:Central Bank Review
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1303070122000208
Description
Summary: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.
ISSN:1303-0701