Based on the multiple seasonal ARIMA model, the monthly PPI data from January 2006 to December 2018 is used to eliminate the tendency and seasonality by the phased and seasonal difference with the help of EVIEWS8.0 software. . Through comparison of indicators,. the model ARIMA(3,1,0)(1,1,1)24 is established to predict PPI from January to June in 2019.The result shows that the model has high prediction accuracy for short-term PPI, which provides the reference for the formulation of relevant economic policies.
薛冬梅.
基于ARIMA乘积季节模型的我国工业品出厂价格指数(PPI)预测
[J]. 吉林化工学院学报, 2019, 36(9): 69-72.
XUE Dongmei.
Prediction in Producer Price Index (PPI) of China Based on Multiple Seasonal ARIMA Model
. Journal of Jilin Institute of Chemical Technology, 2019, 36(9): 69-72.