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A Recap of the 2016 Election Forecasts

The Presidential Forecasts From late June to early September, eight forecasters or teams of forecasters in the PS symposium issued ten presidential election forecasts of the national two-party popular vote (along with the PollyVote composite forecast assembled from an array of different types of forecasts). To avoid any misrepresentation or misunderstanding, it should be emphasized that these forecasts were explicitly of the national two-party popular vote for the major party candidates and not their electoral vote division.2 The final vote count indicates 65.9 million votes were cast for Clinton and about 63.0 million for Trump, providing Clinton with a 2.9 million national popular vote plurality. About 7.8 million votes were cast for other candidates.3 Despite Trump’s electoral vote victory, Clinton received a narrow but clear plurality of the national popular vote.4 Clinton received 51.1% of the two-party popular vote cast nationwide to Trump’s 48.9%. So, how did these forecasts do? With a few exceptions, the accuracy of the presidential vote forecasts ranged from impressive to extraordinary. In my introduction to the October symposium I described how the models weighed the overall conditions, weak economic performance, and general dissatisfaction with the direction of the nation against the pre-campaign preference polls of the candidates. The former favored the Republicans and the latter favored the Democrats, but all of this was within a context of an open-seat race in a period of polarized hyper-competition. On balance, the forecasts expected a Clinton plurality in a tight race. Summing up, I wrote that “the median forecast predicts that Clinton will win 51.1% of the two-party national vote” (Campbell 2016, 653). This calls for an end-zone celebration. Of course, any forecast or set of forecasts that is this accurate depends a great deal on luck, especially in a year with so many outlandish twists and turns, but one needs to be in that vicinity to be so lucky—and we were. Table 1 presents the individual forecasts and errors from our ten statistically estimated historical-fundamentals models along with the PollyVote composite forecast that draws on alternative prediction methods. Of the forecasts produced by the fundamentals models, three missed Clinton’s national vote share by less than a half of one percentage point! These three forecasts were more accurate than either the median of the flurry of mid-campaign “Polls-Plus” forecasts churned out by Nate Silver’s 538 website or the mean of the 10 pre-election polls gathered by Real Clear Politics on the day before the election.5 Seven of the fundamentals forecasts missed the actual vote percentage by only one percentage point or less. The seven include the forecasts from the Jeromes, Lewis-Beck and Tien, Lockerbie as well as the two forecasts by Erikson and Wlezien and the forecasts from my two models. Just beyond these seven are both Holbrook’s forecast and PollyVote. They missed by just under one and a half percentage points. Of the 10 forecasts in the collection, only two erred by more than two percentage points. Abramowitz’s “Time for a Change” forecast under-predicted the vote for Clinton by 2.5 percentage points, though he expected as much. In the write-up of his forecast, Abramowitz essentially anticipated a gap between the normal “time for a change” effect and a much less likely “time for a change to Trump” effect. Norpoth’s early March forecast of a 52.5% Trump popular vote majority produced the largest error of the ten forecasts (3.6 percentage points).6 Aside from the just noted exceptions, 2016 was a great year for the political science presidential vote forecasts. It provided further evidence that presidential elections can be predicted with a good deal of accuracy well in advance of the election with parsimonious, stable, theoretically grounded, and transparent statistical models based on the historical record of the relationship between the election’s fundamentals and the vote.