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DC Field | Value | Language |
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dc.contributor.author | Duangthip Sirikanchanarak | en_US |
dc.contributor.author | Tanaporn Tungtrakul | en_US |
dc.contributor.author | Songsak Sriboonchitta | en_US |
dc.date.accessioned | 2018-09-05T04:26:07Z | - |
dc.date.available | 2018-09-05T04:26:07Z | - |
dc.date.issued | 2018-01-01 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-85037817657 | en_US |
dc.identifier.other | 10.1007/978-3-319-70942-0_45 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037817657&origin=inward | en_US |
dc.identifier.uri | http://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.subject | Computer Science | en_US |
dc.title | The future of global rice consumption: Evidence from dynamic panel data approach | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 753 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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