Welcome to Francis Academic Press

The Frontiers of Society, Science and Technology, 2020, 2(18); doi: 10.25236/FSST.2020.021821.

Analysis of the economic impact of US presidential election on the US and China


Liu Bingrui, Guo Xuerong, Shi Zengquan, Guo Shengxiao, Zhu Yidan

Corresponding Author:
Liu Bingrui

School of Economics and Management, Inner Mongolia University, Hohhot, Inner Mongolia, 010021, China


With the U.S. election drawing to finality, the country will usher in a new leader. In this paper, support vector machine, numerous additive regression and cellular automata models have been established. Spearman correlation coefficient analysis and Dijkstra algorithm have been utilized to conduct multi-field analysis on the influence of different leaders on the economic trends of the two countries. Additionally, numerous additive regression model has been entrenched. In contemplation of determination on the influencing factors related to the ECONOMIC growth of the United States, the support vector machine model has been formulated to procure the effective correlation (0.95<x). Secondly, regarding the endogenous impact of the epidemic, regions have been partitioned in accordance with the severity of the epidemic, and Spearman's algorithm has been availed to scrutinize the correlation amongst different parameters and the economy. Plus, a cellular automata model has been elevated to simulate the epidemic situation. In intellection of this confrontation, we ought to determine whether there lies any influencing factors of the United States on the advancement of Chinese's economy, owing to which first and foremost we have investigated the influencing factors of online access to the U.S. economy which are demonstrative of certain changes as well as the changes of Chinese economic data, and then we are supposed to regress the relationship between both of them, in which we have built the RBF support vector machine (gaussian radial basis) model, carried on the correlation analysis of the relationship. What’s more, we have predicted the circumstances where Biden has been rendered superordinate on the office compared with the Chinese economy.


Support vector machine; multiple linear regression; graph theory; cellular automata model

Cite This Paper

Liu Bingrui, Guo Xuerong, Shi Zengquan, Guo Shengxiao, Zhu Yidan. Analysis of the economic impact of US presidential election on the US and China. The Frontiers of Society, Science and Technology (2020) Vol. 2 Issue 18: 134-142. https://doi.org/10.25236/FSST.2020.021821.


[1] James Galbraith, Jaehee Choi(2020). The consequences of economic inequality for presidential elections in the United States. No.53,pp.86-98.
[2] Michael S Lewis-Beck, Richard Nadeau(2000). French electoral institutions and the economic vote 1 Paper presented at the University of Aarhus Conference, “Economics and Elections: Comparisons and Conclusions”, held in Sandbjerg Gods, Denmark, 23–26 August 1998. 1. no.19(2),pp.171-182.
[3] Ann Mari May(1990). President Eisenhower, Economic Policy, and the 1960 Presidential Election. No.50(2),pp.417-427.
[4] Janet He, Edward Renshaw, Bruce Szelest(1998). Modeling the Outcome of Presidential Elections Using Economic Variables: The Smart Use of Dummy Variables.no.20 (2), pp.251-259.
[5] Stephen Bloom, Stephen Shulman(2011). Interest versus Identity: Economic Voting in Ukrainian Presidential Elections. No.27(4),pp.410-428.
[6] Jacob Tche(2009). Economic Voting in Cameroon.no.28 (3-4), pp.489-503.
[7] David J. Lanoue(1991). Partisan schemas and economic voting: The federal budget deficit and the 1988 presidential election. No. 13(4), pp.285-302.
[8] John W. Goodell, Richard J. McGee, Frank McGroarty (2020). Election uncertainty, economic policy uncertainty and financial market uncertainty: A prediction market analysis. pp.110
[9] Ray R. Sturm(2013). Economic policy and the presidential election cycle in stock returns.no. 37(2),pp.200-215.
[10] Michael A. Brown, Michael Pugliese(2016). Does Economic Activity Slow in Election Years.no. 51(4),pp.260-265.