Proceedings of the 2024 10th International Conference on Humanities and Social Science Research (ICHSSR 2024)

Analysis and Prediction of Shanghai's GDP Based on ARFIMA and ARIMA Models

Authors
Jingyun Xu1, Peng Yuan1, *
1School of Applied Science and Civil Engineering, Beijing Institute of Technology, Zhuhai, Guangdong, 519088, China
*Corresponding author. Email: yuan_peng@bitzh.edu.cn
Corresponding Author
Peng Yuan
Available Online 2 September 2024.
DOI
10.2991/978-2-38476-277-4_174How to use a DOI?
Keywords
GDP; ARFIMA Model; ARIMA Model
Abstract

This article takes Shanghai's GDP as the research object and predicts and analyzes the GDP of Shanghai for the next ten years by comparing two time series models: ARFIMA and ARIMA. Through a comparison of evaluation metrics, it is revealed that there are certain differences between these two models in estimating future GDP. The ARFIMA model performs better than the ARIMA model in terms of AIC value, while the ARIMA model has certain advantages in RMSE.

Copyright
© 2024 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.

Download article (PDF)

Volume Title
Proceedings of the 2024 10th International Conference on Humanities and Social Science Research (ICHSSR 2024)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
2 September 2024
ISBN
978-2-38476-277-4
ISSN
2352-5398
DOI
10.2991/978-2-38476-277-4_174How to use a DOI?
Copyright
© 2024 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

TY  - CONF
AU  - Jingyun Xu
AU  - Peng Yuan
PY  - 2024
DA  - 2024/09/02
TI  - Analysis and Prediction of Shanghai's GDP Based on ARFIMA and ARIMA Models
BT  - Proceedings of the 2024 10th International Conference on Humanities and Social Science Research (ICHSSR 2024)
PB  - Atlantis Press
SP  - 1565
EP  - 1571
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-277-4_174
DO  - 10.2991/978-2-38476-277-4_174
ID  - Xu2024
ER  -