Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)

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Forecast and Analysis of China’s CPI Based on SARIMA Model

Authors
Xiao Zhang1, *
1School of Economics, Wuhan University of Technology, Wuhan, China
*Corresponding author. Email: 944397835@qq.com
Corresponding Author
Xiao Zhang
Available Online 20 December 2022.
DOI
10.2991/978-94-6463-030-5_135How to use a DOI?
Keywords
CPI; Time Series Analysis; SARIMA Model; Forecast
Abstract

The Consumer Price Index (CPI) is an important indicator to measure the level of inflation in our country. It reflects the impact of commodity price changes on the daily lives of residents. It is an important basis for governments at all levels to carry out fiscal policies and the central bank to formulate monetary policies. CPI data reflecting economic phenomena have obvious seasonal time series characteristics. By extracting a total of 59 months from January 2017 to November 2021 in our country, a seasonal differential autoregressive moving average model (SARIMA) is established for empirical analysis and prediction. The results show that SARIMA (0, 1, 0) (0, 1, 1)12 has a high degree of fitting and can better reflect the future trend of my country’s CPI. Based on this, using this model to predict the trend of my country’s CPI in 2022, it is found that my country’s CPI will remain stable at about 102% in 2022, which provides a certain reference for the decision-making of the government, enterprises and other market entities.

Copyright
© 2023 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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Volume Title
Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
20 December 2022
ISBN
10.2991/978-94-6463-030-5_135
ISSN
2589-4919
DOI
10.2991/978-94-6463-030-5_135How to use a DOI?
Copyright
© 2023 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.

Cite this article

risenwbib
TY  - CONF
AU  - Xiao Zhang
PY  - 2022
DA  - 2022/12/20
TI  - Forecast and Analysis of China’s CPI Based on SARIMA Model
BT  - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
PB  - Atlantis Press
SP  - 1354
EP  - 1361
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-030-5_135
DO  - 10.2991/978-94-6463-030-5_135
ID  - Zhang2022
ER  -