Election 2016: What Do the Models Say About Who Will Win in November?

One final point on polling-based forecasts. As rigorous and sophisticated as these models may be, they all have to work with imperfect materials. Polling has become more difficult and polling methods more diverse in recent years. Because of cost and timing, in-person interviews based on area probability samples are not available for election forecasting. Probability-based telephone polls, including those sampling cell phones as well as land lines, face incredibly low response rates, typically in the single digits. It is a leap of faith that those who respond to polls reflect the values, beliefs and preferences of those who do not. Weighting the respondents with Census data to reflect the size of key demographic groups in the voting population, such as age, gender, race, education, and income, is essential and helps improve the representativeness of the data. But it doesn't deal directly with potential differences on important variables within these demographic groups between respondents and non-respondents.

As an illustration of this point, some scholars have found that fluctuations in reported vote intentions are more a consequence of who agrees to be polled than real changes in vote choice. Automated, voice recorded telephone polls confront these problems and many more. Internet polls are increasing in frequency and many rely on opt-in, non-probability samples that require even more elaborate weighting to represent the relevant population. Some of the very best internet polling firms have developed careful procedures to try to counter the bias of not having a random sample, both when respondents are selected and when the data is weighted to make it more representative. Unfortunately, these are more the exception than the rule.

And then there is the problem of identifying likely voters. There is no consensus among polling firms and sponsors on how best to do this and post-election research matching polling respondents with official voting records is not particularly promising.

Additional Forecasting Tools

To supplement the forecasting models based on pre-campaign fundamentals and polling-based state predictions, other sources of data are being utilized. These include:

Betting markets. PredictWise, a composite measure included on The Upshot summary of presidential forecasts, describes itself as follows: "The backbone of predictions on this site are market-based, generated from real money-markets that trade contracts on upcoming events." (See the piece by Phil Wallach on prediction markets.)
Panels of experts. The Monkey Cage, a political science-blog on the Washington Post website, has teamed up with Good Judgment, Inc. to host a forecasting tournament on the 2016 election. Readers of the blog were invited to become participants. Good Judgment has found that ordinary people can be excellent forecasters and 'crowd-sourcing' among thousands of interested observers can produce forecasts that are more accurate than any other indicator.
Wisdom of crowds. Citizen expectations of who is likely to win an upcoming election can be more predictive than their responses to questions on how they intend to vote.
Models of models. A meta-analysis of similar forecasting models (Ensemble Bayesian Model Averaging) or a composite forecast based on a diverse set of forecasting models (PollyVote).

Conclusion

Those looking for certainty in the upcoming presidential election will not be heartened by this review of forecasting models. The polarized structure of American politics shows no sign of being undermined or even sharply altered by the candidacy of Donald Trump, in spite of the warring forces within the GOP. The partisan shape of the electoral landscape in 2016 is strikingly similar to that of 2008 and 2012. Democrats have been boosted by the changing composition of the electorate over the last several decades, most notably the increase in nonwhites and the declining size of the white working class. They enjoy a modest advantage in partisan identification (by Pew's measure, about four points) and now begin each presidential campaign with a substantially larger bloc of relatively safe electoral votes than do the Republicans. But the strongest party voting in decades, reinforced by intense racial and cultural tribal loyalties, guarantees more competitive presidential elections than in years past. In spite of almost unprecedented opposition from Republican Party elites, Trump appears positioned to capture the lion’s share of his party base.

The context of this election apart from the candidates and their campaign is mixed but probably nets out as a small Republican advantage. After eight years with a Democrat in the White House, voters are hankering for change — whatever that might mean to them. The economy has recovered from the Great Recession and unemployment is below five percent but growth is tepid and wages still suffer from long term stagnation. The latest news that US middle class incomes grew faster in 2015 (5.2 percent) than any year in modern history (and the poverty rate fell rate fell by 1.2 points) suggest objective conditions for many families are improving, but subjective measures of present and future economic well-being continue to trail. And try as he might, Barack Obama couldn't avoid being a polarizing president. Nonetheless, his job ratings and personal approval have been in positive territory this election year.

A generic Republican facing a generic Democrat would likely produce a very close election. But no one would accuse Trump or Clinton of being generic candidates. In spite of the intense support he enjoys at large rallies and on social media, Trump is deeply unpopular — and widely viewed by the public as unqualified for the office and temperamentally unsuited to be commander-in-chief. For most of the campaign, that has produced what Vox called a "Trump tax," a measure of the extent to which he is running behind the fundamentals.

While Clinton is accurately viewed as being highly experienced and informed, with a temperament that fits the job, and faces no opposition from leaders within her own party, her unfavorable ratings are just about as high as those of Trump. Saturation media coverage of her private email server and the Clinton Foundation have taken a toll on her public standing, and the 'Trump tax' has declined in recent weeks.

The state-based polling models, betting markets, panels of experts, wisdom of crowds and composite models of diverse forecasting models all point to a likely Clinton victory. But if Trump were to close the polling gap nationally and in the swing states in the next few weeks, a pattern not witnessed this late in the campaign cycle in presidential polling since at least 1952, the forecast of most of these models will move with him.

The debates and fall campaigning (especially in light of her lead in fundraising and campaign organization) should reinforce Clinton's lead and produce a modest victory, not a landslide. The smaller her victory, the less likely Democrats will regain control of the Senate and make solid gains in the House. A Republican Senate would create a huge obstacle to a President Hillary Clinton from day one. (Note that many of these forecasting models predict Senate election outcomes; some do so for the House as well. But that is a subject for another blog.)

What these models cannot do is reduce all uncertainty. The conduct of the campaign and, just as importantly, its coverage in the media during the remaining weeks of the campaign, hold open the possibility, not likelihood, of a President Trump. If the odds of that prospect increase, some longtime Republican voters troubled by Trump's candidacy may decide to see that it does not come to pass.

Tom Mann is resident scholar at IGS. This piece was first published on the Brookings Institution's FixGov blog.

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