2020
DOI: 10.18488/journal.ajard.2020.102.578.586
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Forecasting Import Demand of Table Grapes: Empirical Evidence from Thailand

Abstract: The purpose of this study is to forecast the import demand of table grapes of Thailand using monthly time series from January 2007 to April 2020. The ADF unit root test is used for stationarity checking, and seasonal autoregressive integrated moving average (SARIMA) is applied to forecast the import demand of table grapes. The results revealed that the integration of time series was in the first difference for non-seasonal and seasonal order. The best-fitted forecasting model was SARIMA(1,1,3)(2,1,0)12. The fo… Show more

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Cited by 3 publications
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“…Grapes are popular to be cultivated in the house yard, along with poor management system (Jatuporn et al, 2020). Although it runs on a small business scale, grape farming began to spread and widely cultivated by people in many backgrounds.…”
Section: Introductionmentioning
confidence: 99%
“…Grapes are popular to be cultivated in the house yard, along with poor management system (Jatuporn et al, 2020). Although it runs on a small business scale, grape farming began to spread and widely cultivated by people in many backgrounds.…”
Section: Introductionmentioning
confidence: 99%
“…There are numerous studies using time series analysis to forecast the price and quantity of agricultural commodities, such as Jatuporn and Sukprasert [7] forecasted Thailand's rubber domestic production and export volume using three forecasting techniques, namely, the Box-Jenkins, regression with time trends and seasonal dummies, and exponential smoothing with seasonal additive and multiplicative models. The findings of Jatuporn and Sukprasert [7] revealed that the regression technique with time trends and seasonal dummies was mostly suitable for forecasting domestic production and export volume of rubber in Thailand due to its lowest value of the RMSE statistic. In addition, Co and Boosarawongse [8] forecasted Thailand's export volume of different rice types using three forecasting techniques, namely, artificial neural network (ANN), the Box-Jenkins, and exponential smoothing.…”
Section: Introductionmentioning
confidence: 99%