Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58549
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dc.contributor.authorRoengchai Tansuchaten_US
dc.contributor.authorWoraphon Yamakaen_US
dc.date.accessioned2018-09-05T04:26:10Z-
dc.date.available2018-09-05T04:26:10Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn16113349en_US
dc.identifier.issn03029743en_US
dc.identifier.other2-s2.0-85043991914en_US
dc.identifier.other10.1007/978-3-319-75429-1_31en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85043991914&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58549-
dc.description.abstract© 2018, Springer International Publishing AG, part of Springer Nature. In this paper, we develop a Markov Switching autoregressive distributed lag (MS-ARDL) model in which short- and long-run nonlinearities are introduced. The model is used to investigate the import demand of Nigeria for parboiled rice from Thailand. We demonstrate that the model is estimable by Maximum likelihood estimator and then a reliable long-run inference can be achieved by bound testing regardless of the integration orders of the variables. Furthermore, we first examine the accuracy of the model using a simulation study, and then the salient features of the model are employed to investigate the Thai parboiled rice demand from Nigeria.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleMarkov-Switching ARDL Modeling of Parboiled Rice Import Demand from Thailanden_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.volume10758 LNAIen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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