A New Weighted Food CPI from Scanner Big Data in China

TL;DR

This paper introduces a new weighted food CPI index derived from scanner big data in China, offering higher frequency updates and better reflection of price changes to improve inflation measurement.

Contribution

It presents S-FCPIw, a novel index constructed from scanner data that addresses limitations of traditional CPI in China and enhances real-time inflation tracking.

Findings

S-FCPIw correlates strongly with traditional CPI and Food CPI.

It provides higher frequency and richer dimension insights into price changes.

The index is publicly available and updated weekly.

Abstract

Scanner big data has potential to construct Consumer Price Index (CPI). The study introduces a new weighted price index called S-FCPIw, which is constructed using scanner big data from retail sales in China. We address the limitations of China's CPI especially for its high cost and untimely release, and demonstrate the reliability of S-FCPIw by comparing it with existing price indices. S-FCPIw can not only reflect the changes of goods prices in higher frequency and richer dimension, and the analysis results show that S-FCPIw has a significant and strong relationship with CPI and Food CPI. The findings suggest that scanner big data can supplement traditional CPI calculations in China and provide new insights into macroeconomic trends and inflation prediction. We have made S-FCPIw publicly available and update it on a weekly basis to facilitate further study in this field.