Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/68090
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dc.contributor.authorChonrada Nuntien_US
dc.contributor.authorPetchaluck Boonyakunakornen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2020-04-02T15:18:33Z-
dc.date.available2020-04-02T15:18:33Z-
dc.date.issued2019-10-14en_US
dc.identifier.issn17426596en_US
dc.identifier.issn17426588en_US
dc.identifier.other2-s2.0-85074922985en_US
dc.identifier.other10.1088/1742-6596/1324/1/012107en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074922985&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/68090-
dc.description.abstract© 2019 IOP Publishing Ltd. All rights reserved. The study aims to investigate Thai rice production efficiency with the copula-based stochastic frontier model to draft general statistical data for Thai agriculture development in the future. The empirical results show that land and fertilizer have an indisputably positive and significant effect on rice production. The SFM with Gaussian copula has the lowest value regarding to AIC. The best average TE score belongs to the northern region followed by the central region, the north-eastern region, and the southern region with their average scores of 0.86, 0.819, 0.76 and 0.74, respectively. The interesting point is that, even with highest efficiency score, there is the largest gap between the highest and the lowest scores within central region provinces, followed by north-eastern, central and northern regions with their values of 0.2, 0.18, 0.15 and 0.08, respectively.en_US
dc.subjectPhysics and Astronomyen_US
dc.titleTechnical efficiency of rice production in Thailand: Copula-based stochastic frontier modelen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleJournal of Physics: Conference Seriesen_US
article.volume1324en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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