关键词: CPI, GEKS Price Index, Index Sequence, Window Length, Commodity Substitution Bias

Abstract: The innovative compilation of CPI index based on big data is of great significance for timely understanding the price trend in the new economic era, identifying the inflation crisis, predicting the economic turning point, realizing the modernization of China’s inflation governance and promoting the stable high-quality development of the economy. The GEKS Multilateral Index is a big data-related hotspot price index researched and developed in the international academic community in recent years, but its construction method is quite controversial. Based on the big data of supermarket scanning, in connection with the unresolved problems such as its update method and window length selection, we draw some enlightening conclusions from the theoretical and empirical research: 1) The update methods 2 and 3 have relatively poor application effects. 2) With the increase of the window length, the GEKS sequential price index tends to the unit value, and the GEKS chain indexes under different update methods also show certain convergence. However, the GEKS index’s inflation trend judgment is not affected by the window length, but the choice of update method can lead to different inflation trend prediction results. 3) Update method 4 will present stronger substitution bias with the increase of window length, while there is no obvious substitution bias in method 1. In general, it may be a more reasonable combination for update method 1 and 13 months’ window length to compile GEKS index sequence.

Key words: CPI, GEKS Price Index, Index Sequence, Window Length, Commodity Substitution Bias