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 by using ex-post realizations of banks’ uncertain outputs and the variables intended to capture risk. This is eq...

Full description

Autores:
Malikov, Emir
Restrepo, Diego A.
Kumbhakar, Subal C.
Tipo de recurso:
Fecha de publicación:
2013
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/1001
Acceso en línea:
http://hdl.handle.net/10784/1001
Palabra clave:
Ex-Ante Cost Function
Production Uncertainty
Productivity
Returns to Scale
Risk
Rights
License
Acceso abierto
id REPOEAFIT2_19fec6c8d2df9b910640023fc06cb070
oai_identifier_str oai:repository.eafit.edu.co:10784/1001
network_acronym_str REPOEAFIT2
network_name_str Repositorio EAFIT
repository_id_str
spelling Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees2013-07-11T21:28:39Z2013-05-152013-07-11T21:28:39Zhttp://hdl.handle.net/10784/1001C10D81G21Credit 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 by using ex-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.engUniversidad EAFITEscuela de Economía y FinanzasEstimation of banking technology under credit uncertaintyworkingPaperinfo:eu-repo/semantics/workingPaperDocumento de trabajo de investigacióndrafthttp://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_8042Acceso abiertohttp://purl.org/coar/access_right/c_abf2Ex-Ante Cost FunctionProduction UncertaintyProductivityReturns to ScaleRiskMalikov, EmirRestrepo, Diego A.Kumbhakar, Subal C.emalikov@binghamton.edudrestr16@eafit.edu.cokkar@binghamton.eduORIGINAL2013_19_Diego_A_Restrepo_New_Version.pdf2013_19_Diego_A_Restrepo_New_Version.pdfapplication/pdf826612https://repository.eafit.edu.co/bitstreams/500536d6-89aa-47f9-b2a5-c70a89f557b8/download71b43b69eb5e8b0c606dd30276934020MD53LICENSElicense.txtlicense.txttext/plain; charset=utf-8968https://repository.eafit.edu.co/bitstreams/6827b8d4-97c3-4541-bac8-e3ec6fa14f2e/download4cc960a42e07fca3808fbd6b90ab2a1fMD5210784/1001oai:repository.eafit.edu.co:10784/10012024-03-05 14:06:22.938open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.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
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, Diego A.
Kumbhakar, Subal C.
dc.contributor.author.none.fl_str_mv Malikov, Emir
Restrepo, Diego A.
Kumbhakar, Subal C.
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 by using ex-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 2013
dc.date.available.none.fl_str_mv 2013-07-11T21:28:39Z
dc.date.issued.none.fl_str_mv 2013-05-15
dc.date.accessioned.none.fl_str_mv 2013-07-11T21:28:39Z
dc.type.eng.fl_str_mv workingPaper
info:eu-repo/semantics/workingPaper
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_8042
dc.type.local.spa.fl_str_mv Documento de trabajo de investigación
dc.type.hasVersion.eng.fl_str_mv draft
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/1001
dc.identifier.jel.none.fl_str_mv C10
D81
G21
url http://hdl.handle.net/10784/1001
identifier_str_mv C10
D81
G21
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Acceso abierto
rights_invalid_str_mv Acceso abierto
http://purl.org/coar/access_right/c_abf2
dc.coverage.spatial.eng.fl_str_mv Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees
dc.publisher.spa.fl_str_mv Universidad EAFIT
dc.publisher.department.spa.fl_str_mv Escuela de Economía y Finanzas
institution Universidad EAFIT
bitstream.url.fl_str_mv https://repository.eafit.edu.co/bitstreams/500536d6-89aa-47f9-b2a5-c70a89f557b8/download
https://repository.eafit.edu.co/bitstreams/6827b8d4-97c3-4541-bac8-e3ec6fa14f2e/download
bitstream.checksum.fl_str_mv 71b43b69eb5e8b0c606dd30276934020
4cc960a42e07fca3808fbd6b90ab2a1f
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositorio Institucional Universidad EAFIT
repository.mail.fl_str_mv repositorio@eafit.edu.co
_version_ 1814110362722631680