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Posterior analysis of stochastic frontier models using Gibbs sampling

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorKoop, Gary
dc.contributor.authorSteel, Mark F.J.
dc.contributor.authorOsiewalski, Jacek
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned2009-02-17T10:02:24Z
dc.date.available2009-02-17T10:02:24Z
dc.date.issued1992-12
dc.description.abstractIn this paper we describe the use of Gibbs sampling methods for making posterior inferences in stochastic frontier models with composed error. We show how the Gibbs sampler can greatly reduce the computational difficulties involved in analyzing such models. Our fidings are illustrated in an empirical example.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10016/3677
dc.language.isoeng
dc.relation.ispartofseriesUC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries1992-45-31
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEstadística
dc.subject.otherComposed error models
dc.subject.otherBayesian econometrics
dc.subject.otherGibbs sampling
dc.subject.otherRejection sampling
dc.titlePosterior analysis of stochastic frontier models using Gibbs sampling
dc.typeworking paper*
dspace.entity.typePublication
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