Forecasting CPI with multisource data: The value of media and internet information

Author:

Zheng Tingguo123,Fan Xinyue3ORCID,Jin Wei4,Fang Kuangnan2

Affiliation:

1. Center for Macroeconomic Research Xiamen University Xiamen China

2. School of Economics Xiamen University Xiamen China

3. Wang Yanan Institute for Studies in Economics Xiamen University Xiamen China

4. Penghua Fund Management Co., Ltd. Shenzhen China

Abstract

AbstractUsing a large Chinese news corpus and Internet search data, we conduct an in‐depth out‐of‐sample forecasting study of Consumer Price Index (CPI) with the monthly macroeconomic database. For this purpose, we combine penalized regression and mixed‐frequency data sampling (MIDAS) methods to deal with the mixed‐frequency and high‐dimensional problems. Then we measure the time‐varying contributions of data from different sources and industries via dynamic model averaging. The results show that different types of data all provide enhancement in CPI forecasting, and the inclusion of media and Internet data further improves CPI forecasts' accuracy and timeliness due to their thorough coverage and fast update. In particular, the importance of alternative data is highlighted when the economy experiencing downturn or high uncertainty.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Management Science and Operations Research,Statistics, Probability and Uncertainty,Strategy and Management,Computer Science Applications,Modeling and Simulation,Economics and Econometrics

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