2017Unpublished venueRequires access

The 2016 Presidential Election Popular-Electoral Vote Difference

Joshua Goldstein, David A. Walker

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Abstract

This paper provides models to forecast the popular vote for each of the two major political party candidates in the 2016 US presidential election and to explain the Electoral College outcome. One day prior to the election, the authors published forecasts online (https://finpolicy.georgetown.edu/) predicting Secretary Hillary Clinton would receive between 50.49 and 51.78 percent of the two-party popular vote. These forecasts were developed from economic and political models adapted from the work of Ray Fair. The final, certified vote count shows that Clinton’s share of the two-party popular vote was 51.11 percent. For the second time in the current century, the winner of the popular vote was not elected to the Presidency. Given the difference between the winners of the popular vote and the electoral vote, the authors developed a state-by-state, cross-sectional probit model to explain Donald Trump’s Electoral College victory, based on voters’ economic, racial, and educational characteristics

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What this paper is about

This paper provides models to forecast the popular vote for each of the two major political party candidates in the 2016 US presidential election and to explain the Electoral College outcome. One day prior to the election, the authors published forecasts online (https://finpolicy.georgetown.edu/) predicting Secretary Hillary Clinton would receive between 50.49 and 51.78 percent of the two-party popular vote. These forecasts were developed from economic and political models adapted from the work of Ray Fair. The final, certified vote count shows that Clinton’s share of the two-party popular vote was 51.11 percent. For the second time in the current century, the winner of the popular vote was not elected to the Presidency. Given the difference between the winners of the popular vote and the electoral vote, the authors developed a state-by-state, cross-sectional probit model to explain Donald Trump’s Electoral College victory, based on voters’ economic, racial, and educational characteristics

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Available abstract

This paper provides models to forecast the popular vote for each of the two major political party candidates in the 2016 US presidential election and to explain the Electoral College outcome. One day prior to the election, the authors published forecasts online (https://finpolicy.georgetown.edu/) predicting Secretary Hillary Clinton would receive between 50.49 and 51.78 percent of the two-party popular vote. These forecasts were developed from economic and political models adapted from the work of Ray Fair. The final, certified vote count shows that Clinton’s share of the two-party popular vote was 51.11 percent. For the second time in the current century, the winner of the popular vote was not elected to the Presidency. Given the difference between the winners of the popular vote and the electoral vote, the authors developed a state-by-state, cross-sectional probit model to explain Donald Trump’s Electoral College victory, based on voters’ economic, racial, and educational characteristics

Key concepts: Electoral college, Spoilt vote, Victory, Presidency, Contingent vote, Presidential election, Political science, State (computer science)

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