A Study on Economic Impact in the Context of American Election Based on AHP

Authors

  • Yang Yue North China University of Science and Technology Mathematical Modeling Innovation Lab, Tangshan, Hebei,063210, China; School of Chemical Engineering, North China University of Science and Technology, Tangshan, Hebei, 063210,China
  • Haomiao Niu North China University of Science and Technology Mathematical Modeling Innovation Lab, Tangshan, Hebei,063210, China; School of Chemical Engineering, North China University of Science and Technology, Tangshan, Hebei, 063210,China
  • Zhaoyun Gu School of Electrical Engineering, North China University of Science and Technology, Tangshan, Hebei, 063210,China

DOI:

https://doi.org/10.30564/jesr.v4i2.2775

Abstract

To assess the economic impact of the different policies of the Trump and Biden candidates, we formulate metrics on five aspects: Covid-19 prevention and control measures, environmental protection policies, taxation, health care reform, foreign trade. Moreover, each metric is subdivided into several secondary metrics, making a three-tier hierarchical structure. Take environmental protection policy as an example: Without direct data under Biden’s policies, we collected data on U.S. CO2 emissions and U.S. oil consumption during Obama’s presidency as Biden’s legacy. First, use the analytic hierarchy process (AHP) to select indicators that can reflect the U.S. economy and determine the weight of each indicator. For the U.S. economy, Biden scored 2.6498, Trump 2.3502, suggesting that the election of Biden might make things better for the economy. For China’s economy, Biden scored 0.6810 and Trump 0.3245, meaning Biden could give the Chinese economy more room to grow. To reduce the influence of AHP subjectivity on the results, the Pearson correlation coefficient is introduced to establish the P-AHP model. Take the impact on China’s economy. Biden scored 0.5846 and Trump 0.4154.

Keywords:

AHP, American presidential election, Pearson correlation analysis, Economy

References

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Issue

Vol. 4 , Iss. 2 (April 2021)

Article Type

Articles

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