![]() The conventional wisdom before the election had this reversed, with commentators assuming that Clinton, not Trump would be perceived as the lesser of the evils. In short, outside of California, voters disliked Hillary Clinton more, but they also disliked Donald Trump. Her worst-scoring categories in Kansas Speaks were the same as Trump’s, and Kansans rated her lower on trustworthiness and “understands people like me” than they did Trump. According to respondents in the Kansas Speaks survey, Donald Trump was highly unpopular here, scoring particularly low with our respondents on the matters of trustworthiness and “understanding people like me.” Yet Trump won Kansas easily, and the reason is clear: not only is Kansas a heavily Republican state, but Hillary Clinton was even more unpopular here than was Trump. The results of another poll, in the very “red” state of Kansas where I research, write, and teach, may offer a clue as to why. Yet he is still on the verge of becoming President. Trump did underperform the expectations of these models, presumably due to his unusual personality, behavior, and candidacy. So, in fact, the conventional wisdom was not completely wrong. If John McCain or Mitt Romney had been the Republican nominee, he might very well have gotten the 50%+ of the popular vote predicted by these models. The scholars cited above all predicted a higher popular vote share for the Republican than Trump actually won, while others were even farther off, predicting percentages for the Republican nominee as high as 56% ( Trump actually won just 46.1%). Why were these models so widely ignored? That answer could be summarized as, “but… Donald Trump!” More formally, many commentators (including more than a few who were political scientists or political science-trained) assumed that Donald Trump’s quirky candidacy and high personal negatives meant that the usual partisan-breakdown models used by these political scientists and others simply did not apply this year. The news media’s “horserace” coverage emphasizes polling respondents’ plans to vote for one candidate or another, while political scientists such as Michael Lewis-Beck and Charles Tien, Brad Lockerbie, and Alan Abramowitz, each did what political scientists (as opposed to campaign or media pollsters) usually do-they looked at fundamentals such as the state of the economy, partisan breakdown of the electorate, historical trends, approval of the current President, and voter optimism about the economy, not voters’ opinions of the candidates themselves. Most of those who bucked the media’s conventional wisdom have one thing in common-they looked at numbers affecting partisan breakdown, not numbers for Hillary Clinton and Donald Trump specifically. Quite a few correctly predicted the Republican victory, using various modeling techniques. What lessons can we learn from these polling-based collisions with last year’s electoral iceberg?įirst, it is worth noting that political scientists were not necessarily part of the horse race frenzy. Just before Election Day, however, even Silver’s models leaned toward a Clinton win. The methodology is so advanced, so tested, it is completely indestructible-just like the Titanic! However, in fairness, it should be noted here that Nate Silver, the most popular proponent of this polling-amalgamation strategy, stated repeatedly that Donald Trump has a path to victory. Today, pollsters predict elections based not on a single poll or early returns, but rather on an amalgamation of many polls, plus other data. The methodological sophistication and advanced computer programs used today were not available. ![]() Most notably, telephone polling was in its infancy in 1948. I will never in my life forget spending Election Night watching the needle on the New York Times’ prediction meter move from strongly favoring Clinton to 100% Trump.Ĭomparisons to the classic “Dewey Defeats Truman” headline of 1948 are inevitable, but several differences emerge. The news media and even Saturday Night Live took Clinton’s victory for granted. I joined numerous colleagues in assuming a Hillary Clinton victory. ![]() For political scientists, our “what the…?” moment involves the failure of most public-opinion polls to predict the results of the 2016 election. As I write, Donald Trump is less than two weeks from being inaugurated as President of the United States.
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