Estimation of banking technology under credit uncertainty

Credit risk is crucial to understanding banks’ production technology and should be explicitly accounted for when modeling the latter. The banking literature has largely accounted for risk usingex-post realizations of banks’ uncertain outputs and the variables intended to capture risk. This is equiva...

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Autores:
Malikov, Emir
Restrepo-Tobón, Diego
Kumbhakar, Subal C.
Tipo de recurso:
Fecha de publicación:
2014
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/7619
Acceso en línea:
http://hdl.handle.net/10784/7619
Palabra clave:
Ex-ante cost function
Production uncertainty
Productivity
Returns to scale
Risk
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License
restrictedAccess
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spelling 20142015-11-06T21:15:36Z20142015-11-06T21:15:36Z0377-7332http://hdl.handle.net/10784/761910.1007/s00181-014-0849-zCredit risk is crucial to understanding banks’ production technology and should be explicitly accounted for when modeling the latter. The banking literature has largely accounted for risk usingex-post realizations of banks’ uncertain outputs and the variables intended to capture risk. This is equivalent to estimating an ex-post realization of bank’s production technology which, however, may not reflect optimality conditions that banks seek to satisfy under uncertainty. The ex-post estimates of technology are likely to be biased and inconsistent, and one thus may call into question the reliability of the results regarding banks’ technological characteristics broadly reported in the literature. However, the extent to which these concerns are relevant for policy analysis is an empirical question. In this paper, we offer an alternative methodology to estimate banks’ production technology based on the ex-ante cost function. We model credit uncertainty explicitly by recognizing that bank managers minimize costs subject to given expected outputs and credit risk. We estimate unobservable expected outputs and associated credit risk levels from banks’ supply functions via nonparametric kernel methods. We apply this framework to estimate production technology of U.S. commercial banks during the period from 2001 to 2010 and contrast the new estimates with those based on the ex-post models widely employed in the literature.engSpringer International PublishingEmpirical Economics . Vol. 49, (1), 2014, pp.185-221http://link.springer.com/article/10.1007%2Fs00181-014-0849-zhttp://link.springer.com/article/10.1007%2Fs00181-014-0849-zrestrictedAccess© Springer International Publishing AG, Part of Springer Science+Business MediaAcceso restringidohttp://purl.org/coar/access_right/c_16ecEmpirical Economics . Vol. 49, (1), 2014, pp.185-221Estimation of banking technology under credit uncertaintyarticleinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículopublishedVersionObra publicadahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Ex-ante cost functionProduction uncertaintyProductivityReturns to scaleRiskEconomía y FinanzasFinanzasMalikov, EmirRestrepo-Tobón, DiegoKumbhakar, Subal C.Department of Economics, State University of New York at Binghamton, Department of Economics, St. Lawrence UniversityDepartment of Finance, EAFIT UniversityDepartment of Economics, State University of New York at BinghamtonGrupo de Investigación Finanzas y BancaEmpirical Economics491185221ORIGINALs00181-014-0849-z.pdfs00181-014-0849-z.pdfapplication/pdf1194915https://repository.eafit.edu.co/bitstreams/ffe389f9-4ab7-4320-ac63-bfda5464f02e/download2d3d7e00746012d79b3db5e365ca0d2cMD5110784/7619oai:repository.eafit.edu.co:10784/76192023-03-15 08:27:07.039open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.co
dc.title.eng.fl_str_mv Estimation of banking technology under credit uncertainty
title Estimation of banking technology under credit uncertainty
spellingShingle Estimation of banking technology under credit uncertainty
Ex-ante cost function
Production uncertainty
Productivity
Returns to scale
Risk
title_short Estimation of banking technology under credit uncertainty
title_full Estimation of banking technology under credit uncertainty
title_fullStr Estimation of banking technology under credit uncertainty
title_full_unstemmed Estimation of banking technology under credit uncertainty
title_sort Estimation of banking technology under credit uncertainty
dc.creator.fl_str_mv Malikov, Emir
Restrepo-Tobón, Diego
Kumbhakar, Subal C.
dc.contributor.department.spa.fl_str_mv Economía y Finanzas
Finanzas
dc.contributor.author.spa.fl_str_mv Malikov, Emir
Restrepo-Tobón, Diego
Kumbhakar, Subal C.
dc.contributor.affiliation.spa.fl_str_mv Department of Economics, State University of New York at Binghamton, Department of Economics, St. Lawrence University
Department of Finance, EAFIT University
Department of Economics, State University of New York at Binghamton
dc.contributor.program.spa.fl_str_mv Grupo de Investigación Finanzas y Banca
dc.subject.keyword.eng.fl_str_mv Ex-ante cost function
Production uncertainty
Productivity
Returns to scale
Risk
topic Ex-ante cost function
Production uncertainty
Productivity
Returns to scale
Risk
description Credit risk is crucial to understanding banks’ production technology and should be explicitly accounted for when modeling the latter. The banking literature has largely accounted for risk usingex-post realizations of banks’ uncertain outputs and the variables intended to capture risk. This is equivalent to estimating an ex-post realization of bank’s production technology which, however, may not reflect optimality conditions that banks seek to satisfy under uncertainty. The ex-post estimates of technology are likely to be biased and inconsistent, and one thus may call into question the reliability of the results regarding banks’ technological characteristics broadly reported in the literature. However, the extent to which these concerns are relevant for policy analysis is an empirical question. In this paper, we offer an alternative methodology to estimate banks’ production technology based on the ex-ante cost function. We model credit uncertainty explicitly by recognizing that bank managers minimize costs subject to given expected outputs and credit risk. We estimate unobservable expected outputs and associated credit risk levels from banks’ supply functions via nonparametric kernel methods. We apply this framework to estimate production technology of U.S. commercial banks during the period from 2001 to 2010 and contrast the new estimates with those based on the ex-post models widely employed in the literature.
publishDate 2014
dc.date.issued.none.fl_str_mv 2014
dc.date.available.none.fl_str_mv 2015-11-06T21:15:36Z
dc.date.accessioned.none.fl_str_mv 2015-11-06T21:15:36Z
dc.date.none.fl_str_mv 2014
dc.type.eng.fl_str_mv article
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.local.spa.fl_str_mv Artículo
dc.type.hasVersion.eng.fl_str_mv publishedVersion
dc.type.hasVersion.spa.fl_str_mv Obra publicada
status_str publishedVersion
dc.identifier.issn.none.fl_str_mv 0377-7332
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/7619
dc.identifier.doi.none.fl_str_mv 10.1007/s00181-014-0849-z
identifier_str_mv 0377-7332
10.1007/s00181-014-0849-z
url http://hdl.handle.net/10784/7619
dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.ispartof.spa.fl_str_mv Empirical Economics . Vol. 49, (1), 2014, pp.185-221
dc.relation.isversionof.none.fl_str_mv http://link.springer.com/article/10.1007%2Fs00181-014-0849-z
dc.relation.uri.none.fl_str_mv http://link.springer.com/article/10.1007%2Fs00181-014-0849-z
dc.rights.eng.fl_str_mv restrictedAccess
dc.rights.spa.fl_str_mv © Springer International Publishing AG, Part of Springer Science+Business Media
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.local.spa.fl_str_mv Acceso restringido
rights_invalid_str_mv restrictedAccess
© Springer International Publishing AG, Part of Springer Science+Business Media
Acceso restringido
http://purl.org/coar/access_right/c_16ec
dc.publisher.eng.fl_str_mv Springer International Publishing
dc.source.spa.fl_str_mv Empirical Economics . Vol. 49, (1), 2014, pp.185-221
institution Universidad EAFIT
bitstream.url.fl_str_mv https://repository.eafit.edu.co/bitstreams/ffe389f9-4ab7-4320-ac63-bfda5464f02e/download
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repository.name.fl_str_mv Repositorio Institucional Universidad EAFIT
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