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dc.contributor.authorPathairat Pastpipatkulen_US
dc.contributor.authorParavee Maneejuken_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.description.abstract© Springer International Publishing Switzerland 2015. This paper aimed to measure the welfare of the Thai rice market and provided a new estimation in welfare measurement. We applied the Markov Switching approach to the Seemingly Unrelated Regression model and adopted the Bayesian approach as an estimator for our model. Thus, we have the MSBSUR model as an innovative tool to measure the welfare. The results showed that the model performed very well in estimating the demand and supply equations of two different regimes; namely, high growth and low growth. The equations were extended to compute the total welfare. Then, the expected welfare during the studied period was determined. We found that a mortgage scheme may lead the market to gain a high level of welfare. Eventually, the forecasts of demand and supply were estimated for 10 months, and we found demand and supply would tend to increase in the next few months before dropping around March, 2015.en_US
dc.subjectComputer Scienceen_US
dc.titleWelfare measurement on Thai rice market: A Markov Switching Bayesian Seemingly Unrelated Regressionen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)en_US
article.volume9376en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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