An Analysis of the Economic Impact of US Presidential Elections Based on Principal Component and Logical Regression. (23rd March 2021)

• Record Type: Journal Article
• Authors: Wang, Jing-Jing; Liang, Yan; Su, Jin-Tao; Zhu, Jia-Ming
• Other Names: Wang Shaohui Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-03-23
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/5593967
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Economy is one of the major issues in the United States presidential election campaign. In order to investigate the impact of the US presidential election on the economy, this paper first constructs an analysis model of the economic impact on the United States based on stepwise regression and principal component analysis to analyze the focus of different candidates' attention on the economic issues and its possible impact on the US economy in the election year and after the election; secondly, a Chinese economic impact analysis model based on factor analysis and machine learning logistic regression was constructed to analyze the impact of the US presidential election on the Chinese economy. At the same time, the future economic development of the United States and China based on the time series prediction model is forecast and analyzed, respectively. Finally, the countermeasures and policy suggestions on China's related economic development are put forward.