Forecasting Import Demand for Soybean Meal in Thailand Using Box-Jenkins Method
The objective of this research was to forecast the import demand for soybean meal, which is used in animal feeds, in Thailand using a monthly time series from January 2011 to December 2020 (a total of 120 months). Econometric analysis was employed, which was comprised of: (1) stationary test of the time series using the ADF unit root method; and (2) forecast of the import demand for soybean meal in Thailand using the Box-Jenkins method or SARIMA(p,d,q)(P,D,Q)s model, respectively. The empirical results revealed that: (1) The time series of import demand for soybean meal in Thailand contained non-seasonal and seasonal stationarities at level stage and first differencing order, respectively. (2) The most suitable model to forecast the import demand for soybean meal in Thailand was SARIMA(0,0,1)(0,1,1)12 based on the lowest value of AC and SC statistics. (3) The forecasting import demand for soybean meal in Thailand predicted that the volume in 2021 should increase by 1.71% compared to 2020. The government and related stakeholders should further promote and support domestic soybean production to replace imports from abroad.
Keywords: livestock, forage crop, animal feed, time series forecasting, SARIMA.
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