But to do so is at least a little bit naïve, says Andrew Gelman, a statistician and political scientist at Columbia University. “The polls were off by two percentage points,” Gelman says. Trump was expected to win roughly 48 percent of the two-party vote and ended up with nearly 50 percent. “It just happened to be that this election, two percentage points, plus the distribution of where those points occurred”—errors were greater in states with large populations of white people without college degrees, for example—“were enough to sway the outcome. It was a consequential two percent, but to say the models were far off isn’t quite right.” [...]
Lichtman developed a list of 13 true/false questions, or “keys,” about the incumbent party’s performance in the White House, based on factors such as the administration’s major policy changes, foreign policy successes and failures, the short- and long-term economy, midterm elections, and third parties. Their answers determine the likelihood of the incumbent party staying in office. Answers of “true” to any of the questions favor the incumbent party’s reelection; if the answers to six or more of the questions are “false,” the incumbent party loses. Using this analysis, it became clear to Lichtman that the Democrats were very vulnerable this election cycle, despite what all the polling said. [...]
That’s not to say that polling data can’t be useful, he says. It can help determine whether a third-party candidate is likely to become significant in a given election cycle, or be used to assess public opinion on presidential initiatives (Lichtman cites the Iran nuclear deal by way of example). But polls have no place in helping to predict outcomes in national elections, and should not be used to do so in the media’s elections coverage, he says. “Next election, send all the pollsters off to a beautiful island. They can have a nice, long vacation.”
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