17:23 Nov. 11, 2016
Pollsters stumbled largely because the popular vote metric itself is of limited utility and cannot predict the outcome of the Electoral College
Two days ago, pollsters and statisticians gave Hillary Clinton odds of between 75 and 99 percent of winning the U.S. presidential election. How did so many get it so wrong?
In hindsight, the polling consensus went astray in two major ways.
The media, including Reuters, pumped out two kinds of poll stories. Some were national surveys designed to estimate the entire country's popular vote, but not the outcome in individual states, where the contest is actually decided. These polls actually got the big picture right: Clinton won more overall votes than President-elect Donald Trump - but not by as much as the polling averages predicted, and not where she needed to.
News organizations also produced a blizzard of stories meant to calculate the probability of victory for the two candidates. These calculations were predicated on polls of individual states. In hindsight, though, the stories seem to have overstated Clinton's chances for a win by failing to see that a shift in voting patterns in some states could show up in other, similar states.
In part, this is because polling analysts got the central metaphor wrong.
U.S. presidents are chosen not by the national popular vote, but in the individual Electoral College contests in the 50 states and Washington D.C. In calculating probable outcomes, election predictors generally treated those 51 contests as completely separate events – as unrelated to one another as a series of 51 coin tosses.
But that's not how elections work in the United States. Voting trends that appear in one state - such as a larger-than-expected Republican shift among rural voters - tend to show up in other states with similar demographic make-ups.