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dc.contributor.authorVarith Pipitpojanakarnen_US
dc.contributor.authorParavee Maneejuken_US
dc.contributor.authorWoraphon Yamakaen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T02:57:56Z-
dc.date.available2018-09-05T02:57:56Z-
dc.date.issued2016-01-01en_US
dc.identifier.issn16113349en_US
dc.identifier.issn03029743en_US
dc.identifier.other2-s2.0-85005938324en_US
dc.identifier.other10.1007/978-3-319-49046-5_59en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85005938324&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/55565-
dc.description.abstract© Springer International Publishing AG 2016. The purpose of this paper is to evaluate the efficiency of agricultural production in Asia and analyze the production function of Asian countries. Methodologically, we employ the stochastic frontier model with the concern about dependency between two-sided error term and one-sided inefficiency. Likewise, we try to improve the performance of the standard stochastic frontier model by applying quantile regression to the frontier production function. Therefore, this paper introduces the model called Copula-based stochastic frontier quantile model as an alternative tool for this issue. The accuracy of this model is proved through a simulation study before applying to the agricultural production data of Asia.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleAnalysis of agricultural production in Asia and measurement of technical efficiency using copula-based stochastic frontier quantile modelen_US
dc.typeBook Seriesen_US
article.title.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
article.volume9978 LNAIen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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