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dc.contributor.authorSongsak Sriboonchittaen_US
dc.contributor.authorJianxu Liuen_US
dc.contributor.authorAree Wiboonpongseen_US
dc.contributor.authorThierry Denoeuxen_US
dc.date.accessioned2018-09-05T03:35:44Z-
dc.date.available2018-09-05T03:35:44Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn0888613Xen_US
dc.identifier.other2-s2.0-84987934284en_US
dc.identifier.other10.1016/j.ijar.2016.08.006en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84987934284&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/57171-
dc.description.abstract© 2016 Elsevier Inc. In the standard stochastic frontier model with sample selection, the two components of the error term are assumed to be independent, and the joint distribution of the unobservable in the selection equation and the symmetric error term in the stochastic frontier equation is assumed to be bivariate normal. In this paper, we relax these assumptions by using two copula functions to model the dependences between the symmetric and inefficiency terms on the one hand, and between the errors in the sample selection and stochastic frontier equation on the other hand. Several families of copula functions are investigated, and the best model is selected using the Akaike Information Criterion (AIC). The methodology was applied to a sample of 200 rice farmers from Northern Thailand. The main findings are that (1) the double-copula stochastic frontier model outperforms the standard model in terms of AIC, and (2) the standard model underestimates the technical efficiency scores, potentially resulting in wrong conclusions and recommendations.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleA double-copula stochastic frontier model with dependent error components and correction for sample selectionen_US
dc.typeJournalen_US
article.title.sourcetitleInternational Journal of Approximate Reasoningen_US
article.volume80en_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsPrince of Songkla Universityen_US
article.stream.affiliationsUniversite de Technologie de Compiegneen_US
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