Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58543
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dc.contributor.authorDuangthip Sirikanchanaraken_US
dc.contributor.authorTanaporn Tungtrakulen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T04:26:07Z-
dc.date.available2018-09-05T04:26:07Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1860949Xen_US
dc.identifier.other2-s2.0-85037817657en_US
dc.identifier.other10.1007/978-3-319-70942-0_45en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037817657&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58543-
dc.description.abstract© Springer International Publishing AG 2018. This study investigates the future outlook of global rice consumption using dynamic panel data regression (DPD) with penalised fixed effect model. The three main factors affecting rice consumption include previous rice demand, GDP per capita, and world rice price. The data set covers 73 countries that is almost 80% of world rice consumption from 1960 to 2015. We separate these countries into 4 groups based on income levels classified by the World Bank including low income, lower middle-income, upper middle-income, and high income. The results show that, at the global scale, rice consumption is expected to be slightly higher. Such demand is driven by rising demand from the upper middle- and high income countries, while it is offset by the lower demand from lower middle- and low income countries.en_US
dc.subjectComputer Scienceen_US
dc.titleThe future of global rice consumption: Evidence from dynamic panel data approachen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume753en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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