Electoral College bias and the 2020 presidential election

Author:

Erikson Robert S.ORCID,Sigman KarlORCID,Yao LinanORCID

Abstract

Donald Trump’s 2016 win despite failing to carry the popular vote has raised concern that 2020 would also see a mismatch between the winner of the popular vote and the winner of the Electoral College. This paper shows how to forecast the electoral vote in 2020 taking into account the unknown popular vote and the configuration of state voting in 2016. We note that 2016 was a statistical outlier. The potential Electoral College bias was slimmer in the past and not always favoring the Republican candidate. We show that in past presidential elections, difference among states in their presidential voting is solely a function of the states’ most recent presidential voting (plus new shocks); earlier history does not matter. Based on thousands of simulations, our research suggests that the bias in 2020 probably will favor Trump again but to a lesser degree than in 2016. The range of possible outcomes is sufficiently wide, however, to even include some possibility that Joseph Biden could win in the Electoral College while barely losing the popular vote.

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

Reference4 articles.

1. A. Gelman , J. Katz , G. King , “Empirically evaluating the electoral college” in Rethinking the Vote: The Politics and Prospects of American Electoral Reform, A. N. Crigler , M. R. Just , E. J. McCaffery , Eds. (Oxford University Press, New York, NY, 2004), pp. 75–88.

2. N. R. Miller , “Election inversions by the US electoral college” in Electoral Systems: Paradoxes, Assumptions, and Procedures, D. S. Felsenthal , M. Mosh’e , Eds. (Springer, Heidelberg, Germany, 2012), pp. 93–127.

3. Are presidential inversions inevitable? Comparing eight counterfactual rules for electing the president;Cervas;Soc. Sci. Q.,2019

4. M. Geruso , D. Spears , I. Talesara , Inversions in US Presidential Elections 1826-2016. NBER Working paper 26247 (2020). https://www.nber.org/papers/w26247. Accessed 5 October 2020.

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3