Similarly, if the popular vote is a tie or Trump leads slightly in the popular vote, Biden would have a remote chance of winning, overturning the narrative that the Electoral College favors Republicans. Based on our modeling, Trump would have a remote chance of winning even if his support is as slim as 48% of the popular vote. Additionally, while 51 to 49 is the approximate division of the popular vote at which each candidate has an equal shot at winning, the Electoral College verdict remains probabilistic. The inflection point between a probable Democratic or Republican win in the Electoral College is not at a 50 to 50 popular vote but rather, in the range of 51% Democrat and 49% Republican. When applied to 2020, we find that the Electoral College’s pro-Republican bias that emerged in 2016 persists at about half as severe as in 2016. Our results consist of probabilistic distributions of discrete Electoral Vote divisions. Using past presidential elections as the testing grounds, we have verified a simulation procedure for forecasting the Electoral College for a given popular vote for a particular year. Even with 52.0% of the popular vote, Obama loses the simulated 2012 Electoral College 3.36% of the time. Still, even with knowing the seemingly best estimation equation, the actual popular vote, and the state divisions during the previous election year, getting the Electoral College winner and popular vote winner to match has elements of a lottery. We replicate similarly benign results for earlier elections. The actual Electoral College division (332 Obama, 206 Romney) was near the center of the simulated outcomes. 1 2012, the state vote divisions in 2008, and the 2012 popular vote of 52.0% Barack Obama and 48.0% Mitt Romney. 2 B shows the retrospectively likely 2012 Electoral College division when using Eq. For elections leading up to 2016, the actual vote margins were well within the range of the after-the-fact simulated forecasts. 1 t, the distributions show the range of likely outcomes in the Electoral College. In other words, knowing the exact popular vote in election year t, the partisan division of states in election year t − 4, plus Eq. The simulated Electoral College outcomes are conditional on the actual national popular vote as explained above. 2 shows the simulations for the nine elections. 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.įig. 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. 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. The potential Electoral College bias was slimmer in the past and not always favoring the Republican candidate. We note that 2016 was a statistical outlier. 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. 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.
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