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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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
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author Abdus Samad
Vaughn S. Armstrong
author_facet Abdus Samad
Vaughn S. Armstrong
author_sort Abdus Samad
collection DOAJ
description 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.
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spelling doaj.art-06e352cf55634e31985da972a9b26cf42022-12-22T04:06:03ZengElsevierCentral Bank Review1303-07012022-09-01223119127Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failuresAbdus Samad0Vaughn S. Armstrong1Corresponding author.; Department of Finance and Economics Utah Valley University 800 W University Pkwy Orem, UT, 84058, USADepartment of Finance and Economics Utah Valley University 800 W University Pkwy Orem, UT, 84058, USAThis 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.http://www.sciencedirect.com/science/article/pii/S1303070122000208G20G21
spellingShingle Abdus Samad
Vaughn S. Armstrong
Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failures
Central Bank Review
G20
G21
title Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failures
title_full Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failures
title_fullStr Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failures
title_full_unstemmed Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failures
title_short Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 U.S. bank failures
title_sort bootstrap dea management efficiency and early prediction of bank failure evidence from 2008 2009 u s bank failures
topic G20
G21
url http://www.sciencedirect.com/science/article/pii/S1303070122000208
work_keys_str_mv AT abdussamad bootstrapdeamanagementefficiencyandearlypredictionofbankfailureevidencefrom20082009usbankfailures
AT vaughnsarmstrong bootstrapdeamanagementefficiencyandearlypredictionofbankfailureevidencefrom20082009usbankfailures