Research on the Influence of Volatility of International Energy Commodity Futures Market on CPI in China - Keyao Lin; Chao Xun; Fei Wang; Angela Chi Chao; Zhenyu Du (Complexity)
This article analyses the transmission path of the international commodity futures market’s impact on the Chinese economy. We use the MIDAS model and daily data to predict China’s CPI in real time. Empirical analysis results show that (1) the influence of high-frequency explanatory variables on low-frequency CPI is different. The optimal lag orders of domestic high-frequency variables are all around 23, which can be regarded as one month in practice, indicating that their CPI influence takes one month to show. (2) Both the univariate MIDAS model and the multivariate MIDAS combined prediction model have good performance in prediction accuracy. (3) The predicted results of the multivariate MIDAS combined prediction model for CPI in China’s normal months are relatively excellent. However, when exceptional circumstances occur, the prediction results will show a specific deviation, and the prediction accuracy will also be reduced. Finally, some feasible suggestions are put forward according to the research results.