So, back to the main question: How were all the pollsters so wrong, again, even after the soul searching and methodological recalibrating that followed 2016?
The first answer is that public opinion researchers haven't learned from their past mistakes.
First, pollsters almost surely underestimated what is called a "nonresponse bias," which is a fancy term for saying that the
voters who participated in the surveys had different opinions than those who did participate — i.e., either Trump voters weren't
contacted, refused to respond or chose not to answer truthfully. A
Second, there is one polling prediction device that is regularly overlooked and misunderstood: approval ratings. A quick glance would show you that Trump has the lowest average approval rating in history at only 41%. The average for reelected presidents since 1980 is 54.5% — almost 14 percentage points higher! Since recording approval ratings began, every reelected president has had over a 50% approval rating when reelected or an upward trend over 30 days before the election.
This would clearly suggest that Trump didn't have a chance of winning — but there was a clear asterisk.
As I discussed in 2019 and last month, we should care less about the raw numbers than about the trend; we can't compare Trump's approval ratings to past presidents, we have to compare the highs and lows over time. In that case, Trump has the smallest difference in spread ever recorded. In other words, Trump had what is arguably the strongest base in recent history. Furthermore, a basic statistical analysis shows that Trump trended toward higher and higher approval ratings since he took office — only gaining in his base.
Third, pollsters have not gotten any better at estimating the margin of error in their polling according to a piece out of the Harvard Data Science Review last week. Pollsters don't ask every American for their vote decision, but instead they ask a smaller portion of the population and infer from that what the entire population is going to do. That means there is inevitably plus or minus error in their predictions.
Overall, not a single one of these three issues was enough to push the election to Trump, but combined, they threw off pollsters' models. Again.
(COMMENT, BELOW)
Liberty Vittert
New York Daily News
(TNS)
Liberty Vittert is a professor of the practice of data science at the Olin Business School at the Washington University in St. Louis and the feature editor of the Harvard Data Science Review.