Estimation of banking technology under credit uncertainty

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dc.citation.epage221
dc.citation.issue1
dc.citation.journalTitleEmpirical Economicseng
dc.citation.spage185
dc.citation.volume49
dc.contributor.affiliationDepartment of Economics, State University of New York at Binghamton, Department of Economics, St. Lawrence Universityspa
dc.contributor.affiliationDepartment of Finance, EAFIT Universityspa
dc.contributor.affiliationDepartment of Economics, State University of New York at Binghamtonspa
dc.contributor.authorMalikov, Emirspa
dc.contributor.authorRestrepo-Tobón, Diegospa
dc.contributor.authorKumbhakar, Subal C.spa
dc.contributor.departmentEconomía y Finanzasspa
dc.contributor.departmentFinanzasspa
dc.contributor.programGrupo de Investigación Finanzas y Bancaspa
dc.date2014
dc.date.accessioned2015-11-06T21:15:36Z
dc.date.available2015-11-06T21:15:36Z
dc.date.issued2014
dc.description.abstractCredit 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.eng
dc.identifier.doi10.1007/s00181-014-0849-z
dc.identifier.issn0377-7332
dc.identifier.urihttp://hdl.handle.net/10784/7619
dc.language.isoengeng
dc.publisherSpringer International Publishingeng
dc.relation.ispartofEmpirical Economics . Vol. 49, (1), 2014, pp.185-221spa
dc.relation.isversionofhttp://link.springer.com/article/10.1007%2Fs00181-014-0849-z
dc.relation.urihttp://link.springer.com/article/10.1007%2Fs00181-014-0849-z
dc.rightsrestrictedAccesseng
dc.rights© Springer International Publishing AG, Part of Springer Science+Business Mediaspa
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccesseng
dc.rights.localAcceso restringidospa
dc.sourceEmpirical Economics . Vol. 49, (1), 2014, pp.185-221spa
dc.subject.keywordEx-ante cost functioneng
dc.subject.keywordProduction uncertaintyeng
dc.subject.keywordProductivityeng
dc.subject.keywordReturns to scaleeng
dc.subject.keywordRiskeng
dc.titleEstimation of banking technology under credit uncertaintyeng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.type.hasVersionObra publicadaspa
dc.type.localArtículospa

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