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A Bayesian semi-parametric approach to stochastic frontier models with inefficiency heterogeneity

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dc.affiliation.dptoUC3M. Departamento de EstadĂ­stica
dc.affiliation.grupoinvUC3M. Grupo de InvestigaciĂ³n: TĂ©cnicas no ParamĂ©tricas y de ComputaciĂ³n Intensiva en EstadĂ­stica
dc.affiliation.grupoinvUC3M. Grupo de InvestigaciĂ³n: ModelizaciĂ³n EstadĂ­stica y AnĂ¡lisis de Datos
dc.affiliation.institutoUC3M. Instituto Flores de Lemus
dc.contributor.authorDeng, Yaguo
dc.contributor.authorWiper, Michael Peter
dc.contributor.authorLopes Moreira Da Veiga, MarĂ­a Helena
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de EstadĂ­sticaes
dc.date.accessioned2024-04-24T08:28:53Z
dc.date.available2024-04-24T08:28:53Z
dc.date.issued2024-04-23
dc.description.abstractIn this chapter, we present a semiparametric Bayesian approach for stochastic frontier (SF) models that incorporates exogenous covariates into the inefficiency component by using a Dirichlet process model for conditional distributions. We highlight the advantages of our method by contrasting it with traditional SF models and parametric Bayesian SF models using two different applications in the agricultural sector. In the first application, the accounting data of 2,500 dairy farms from five countries are analyzed. In the second case study, data from forty-three smallholder rice producers in the Tarlac region of the Philippines from 1990 to 1997 are analyzed. Our empirical results suggest that the semi-parametric Bayesian stochastic frontier model outperforms its counterparts in predictive efficiency, highlighting its robustness and utility in different agricultural contexts.en
dc.format.extent35
dc.identifier.issn2387-0303
dc.identifier.publicationissue24-03
dc.identifier.urihttps://hdl.handle.net/10016/43837
dc.identifier.uxxiDT/0000002118
dc.language.isoeng
dc.relation.ispartofseriesWorking paper Statistics and Econometricsen
dc.relation.ispartofseries24-03
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ecienciaEstadĂ­stica
dc.subject.otherBayesian semi-parametric inference
dc.subject.otherEfficiency
dc.subject.otherHeterogeneity
dc.subject.otherProduction function
dc.subject.otherStochastic frontier analysis
dc.titleA Bayesian semi-parametric approach to stochastic frontier models with inefficiency heterogeneity
dc.typeworking paper
dc.type.hasVersionVoR
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoverybd4ac1a2-7c6b-4c36-8567-42f5cefd2eb8
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