Application of Big Data Analysis in Macroeconomic Models: A Case Study on Consumer Price Index (CPI) Forecasting

DOI

10.2991/978-94-6463-702-1_51How to use a DOI?

Keywords

Big Data Analysis; Machine Learning; Macroeconomic Models; Consumer Price Index (CPI) Forecasting; High-Dimensional Data; Model Interpretability; High-Frequency Indicators; Economic Policy Impact; Real-Time Forecasting

Abstract

Investigating the synergy between big data analysis and machine learning within the realm of macroeconomic modeling, the study delves into the forecasting of the consumer price index (CPI). It underscores the importance of harnessing high-dimensional data to develop machine learning models that are not only predictive but also interpretable, thereby enhancing the precision of CPI predictions. A comparative analysis of the efficacy of various machine learning models, with an emphasis on Random Forest and XGBoost for long-term forecasting, is presented. The research extends to the construction of high-frequency economic indicators from internet-based price data and the optimization of traditional economic metrics through big data insights. Theoretical derivations and empirical analyses, complemented by five pivotal visualizations, reveal the strengths and limitations of current methodologies and point the way for future investigative paths. The study concludes with the implications of these findings for the evolution of macroeconomic modeling and the formulation of economic policies, highlighting the significant role big data can play in these domains.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhentao Jiang
AU  - Hao Zheng
AU  - Yu Yan
AU  - Xinyue Zhang
AU  - Zhe Wang
PY  - 2025
DA  - 2025/05/05
TI  - Application of Big Data Analysis in Macroeconomic Models: A Case Study on Consumer Price Index (CPI) Forecasting
BT  - Proceedings of the 2025 10th International Conference on Financial Innovation and Economic Development (ICFIED 2025)
PB  - Atlantis Press
SP  - 485
EP  - 496
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-702-1_51
DO  - 10.2991/978-94-6463-702-1_51
ID  - Jiang2025
ER  -