Time Series Forecasting with Classical Decomposition Method: Jasmine Rice Exportation of Thailand

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Nitinai Rungjindarat
Sarun Thatsakaniwet


The aim of this paper is to study the trend, seasonal deviance and forecasting for the exportation value of jasmine rice in Thailand between year 2018 - 2019. The quarterly data is used for conducting the forecast model. The data are divided into two sets, first is the training data. Second is the testing data obtained from the Office of Agricultural Economics. Time Series Analysis is composed by classical decomposition method. The study found that the forecast model is extremely accurate since the Mean Absolute Percentage Error of the training data has resulted in 6.42% and Mean Absolute Percentage Error of the testing data is 3.09%. The exportation value of jasmine rice in Thailand has the tendency to decline together with the occurrence of seasonal deviance. The exportation value is highest in the fourth quarter (17.63% more than usual) and found to be lowest in the second quarter (10.66% less than usual)

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How to Cite
Rungjindarat, N. ., & Thatsakaniwet , S. . (2020). Time Series Forecasting with Classical Decomposition Method: Jasmine Rice Exportation of Thailand. Dusit Thani College Journal, 13(2), 283–293. Retrieved from https://so01.tci-thaijo.org/index.php/journaldtc/article/view/241072
Research Article


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