Author(s)

Junchen Li ¹

Affiliation(s)

¹ School of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, 400067, China

Corresponding Author

Junchen Li

ABSTRACT

This paper explores the application of matrix factor models to analyze high-dimensional time series data on commodity retail price indicators across Chinese provinces. The research addresses the gap in existing literature that often focuses on simpler models and smaller datasets, which do not adequately capture the complex interdependencies and structural dynamics inherent in provincial economic data. By employing matrix factor models, this study leverages the inherent matrix structure of the data for significant dimensional reduction, enhancing the clarity and reliability of the analysis. The findings provide a detailed insight into regional economic behaviors and market conditions, offering a nuanced understanding that is crucial for precise macroeconomic policy-making and financial risk management. The study demonstrates the potential of matrix factor models to effectively manage high-dimensional datasets, thereby contributing valuable tools for economists and policymakers to better predict and respond to economic fluctuations across different regions. This research is essential for designing targeted interventions that promote balanced regional development and economic resilience, particularly in the diverse economic landscape of China.

KEYWORDS

Matrix Factor Models, Commodity Retail Prices, High-dimensional Data Analysis, Macroeconomic Policy, Financial Risk Management

CITE THIS PAPER

Junchen Li, Analysis of Commodity Retail Price Indicators in Chinese Provinces Based on Matrix Factor Model. Financial Engineering and Risk Management (2024) Vol. 7: 100-109. DOI: http://dx.doi.org/10.23977/ferm.2024.070313.

REFERENCES

[1] Liu, X., Wang, J., & Chen, Y. (2020) Urbanization and Its Impact on Retail Sales and Financial Stability. Journal of Urban Economics, 34, 123-145.
[2] Zhang, H., Li, S., & Xu, W. (2019) The Influence of Regional Policies on Economic Performance and Risk. Regional Studies, 53, 789-812.
[3] Xu, Q., Zhao, L., & Tang, M. (2018) Regional Consumption Differences and Economic Resilience. Economic Research Journal, 45, 332-348.
[4] Wang, L., Sun, Y., & Liu, Z. (2021) Local Economic Conditions and Financial Environments. Journal of Financial Studies, 29, 215-230.
[5] Wang, D., Liu, X., & Chen, R. (2016) Factor Models for Matrix-Valued High-Dimensional Time Series. Journal of Econometrics.
[6] Chen, E. Y., & Chen, R. (2019) Modeling Dynamic Transport Network with Matrix Factor Models: with an Application to International Trade Flow. arXiv: Econometrics.
[7] Tang, C., & Shi, Y. (2021) Forecasting High-Dimensional Financial Functional Time Series: An Application to Constituent Stocks in Dow Jones Index. Journal of Risk and Financial Management.
[8] Davis, C. (1963) The Rotation of Eigenvectors by a Perturbation. Journal of Mathematical Analysis and Applications, 11, 20-27. 

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