Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/76430
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dc.contributor.authorJittima Singvejsakulen_US
dc.contributor.authorYaovarate Chaovanapoonpholen_US
dc.contributor.authorBudsara Limnirankulen_US
dc.date.accessioned2022-10-16T07:09:56Z-
dc.date.available2022-10-16T07:09:56Z-
dc.date.issued2021-09-01en_US
dc.identifier.issn22277099en_US
dc.identifier.other2-s2.0-85117045605en_US
dc.identifier.other10.3390/economies9030132en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85117045605&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/76430-
dc.description.abstractThailand is a significant global exporter of cassava, of which cassava chips are the main export products. Moreover, China was the most important export market for Thailand from 2000 to 2020. However, during that period, Thailand confronted fluctuations in the cassava product price, and cassava chips were a product with significant price volatility, adapting to changes in export volumes. This study aims to analyze the volatility of the price of cassava chips in Thailand from 2010 to 2020. The data were collected monthly from 2010 to 2020, including the price of cassava chips in Thailand (Y), the volume of cassava China imported from Thailand (X1), the price of the cassava chips that China imported from Thailand (X2), the price of the cassava starch that China imported from Thailand (X3), the substitute crop price for maize (X4), the substitute crop price for wheat (X5), and Thailand’s cassava product export volume (X6). The volatility and the factors affecting the volatility in the price of cassava chips were calculated using Bayesian GARCH-X. The results indicate that the increase in X1, X2, X3, X4, and X6 led to an increase in the rate of change in cassava chip price volatility. On the other hand, if the substitute crop price for wheat (X5) increases, then the rate of change in the volatility of the cassava chip price decreases. Therefore, the government’s formulation of an appropriate cassava policy should take volatility and the factors affecting price volatility into account. Additionally, the government’s formulation of agricultural policy needs to consider Thailand’s macro-environmental factors and its key trading partners, especially when these environmental factors signal changes in the price volatility of cassava.en_US
dc.subjectEconomics, Econometrics and Financeen_US
dc.subjectSocial Sciencesen_US
dc.titleModeling the price volatility of cassava chips in thailand: Evidence from bayesian garch-x estimatesen_US
dc.typeJournalen_US
article.title.sourcetitleEconomiesen_US
article.volume9en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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