Proceedings of the 2022 3rd International Conference on Big Data Economy and Information Management (BDEIM 2022)

U.S. GDP Detrended Analysis

Authors
Pan Hu1, *, Peiyao Ji2, Huishan Xu3, Xingyu Shi4, Yi Wu5
1University of Cincinnati, Cincinnati, OH, 45202, USA
2University of Glasgow, Glasgow, G12 8QQ, UK
3Qingdao No. 58 Middle School, Qingdao, 266100, China
4Huaer Zizhu Academy, Shanghai, 201102, China
5Suzhou Science and Technology Town Foreign Language High School, Suzhou, 215001, China
*Corresponding author. Email: hupa@mail.uc.edu
Corresponding Author
Pan Hu
Available Online 29 March 2023.
DOI
10.2991/978-94-6463-124-1_45How to use a DOI?
Keywords
Gross Domestic Product; Detrended; Cyclical; Standard Deviation; Correlation
Abstract

This paper uses a detrending approach to examine the factors influencing U.S. GDP. We selected U. S GDP data from 1981 to 2021 from the Bureau of Economic Analysis to make the sample reliable. We estimate factors that affect GDP, including consumption, investment, and government spending. We analyzed the trend of the data by adding the linear regression method. Through the detrending treatment of the influencing factors, we found that taking a short-term perspective; Investment is more volatile than consumption, so the government should stimulate investment. From a long-term perspective, it would be more prudent for the government to encourage consumption because consumption is less volatile than investment. There will be steady growth in the GDP. GDP influences government spending over two years.

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 3rd International Conference on Big Data Economy and Information Management (BDEIM 2022)
Series
Advances in Economics, Business and Management Research
Publication Date
29 March 2023
ISBN
10.2991/978-94-6463-124-1_45
ISSN
2352-5428
DOI
10.2991/978-94-6463-124-1_45How 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

TY  - CONF
AU  - Pan Hu
AU  - Peiyao Ji
AU  - Huishan Xu
AU  - Xingyu Shi
AU  - Yi Wu
PY  - 2023
DA  - 2023/03/29
TI  - U.S. GDP Detrended Analysis
BT  - Proceedings of the 2022 3rd International Conference on Big Data Economy and Information Management (BDEIM 2022)
PB  - Atlantis Press
SP  - 376
EP  - 384
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-124-1_45
DO  - 10.2991/978-94-6463-124-1_45
ID  - Hu2023
ER  -