How can anyone accurately estimate the outcome of an election more than three months ahead of time — before the conventions, the debates, and the twists and turns of the fall campaign? Primarily because Abramowitz’s forecasting model disregards the fall campaign altogether. His method acknowledges something that political operatives, journalists and candidates rarely do: Presidential campaigns don’t matter much in determining winners and losers.
Despite all the noise from the campaign trail — from the onslaught of TV ads to the daily rallies to the frenzied news coverage — factors beyond either candidate’s control largely determine the result, according to this school of thought. So much is already baked into a presidential contest that even the best managed and most effective campaign (or the most incompetent one) can’t move the needle too far.
This idea has been around since at least the 1940s and has been so thoroughly studied that it has its own wonky name, the Minimal Effects Model. Simply stated, the model says that presidential campaigns have a highly limited effect on how people vote. Because of partisan loyalties and other structural factors, millions of voters have made up their minds long before the most intense electioneering begins, leaving only a disengaged few for the candidates to persuade.
“When you’re in the middle of a campaign, there’s a tendency for people, especially the media, to overestimate the importance of certain events,” Abramowitz says. These include high-profile gaffes, vice presidential selections, controversial ads and other moments that capture so much attention.
Except, he adds, “those things have no measurable impact [on voters’ decisions]. The media are interested in getting people’s attention, but a lot of the stories you read or see are focusing on things that are trivial. The way campaigns play out is largely determined by fundamentals.”
In his case, the “fundamentals” are broad measures of the electorate’s happiness or dissatisfaction. Abramowitz plugs just three variables into his forecasting model — the president’s approval rating in mid-year, economic growth in the second quarter, and whether either party is seeking a third consecutive term (he gives the incumbent party’s candidate a bump if the answer is no).
Other forecasters, such as James E. Campbell of the State University of New York at Buffalo, have achieved results similar to Abramowitz’s by considering a sequence of Gallup polls several months before Election Day. Yale economist Ray C. Fair, the author of “Predicting Presidential Elections and Other Things,” has accurately modeled 21 of the 24 elections since 1916 with a method that combines economic growth, inflation and the effect of incumbency.