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

This year, however, the release of forecasts based on these models just before Labor Day did little to reduce the uncertainty. There was no consensus on who would win much less on the size of the victor's margin. Abramowitz's model forecasts a narrow Trump victory but he expects it to fail this year. Why? The model assumes that both parties will nominate mainstream candidates capable of unifying their parties and that both candidates will run reasonably competent campaigns. The nomination of Trump by the Republican Party, in Abramowitz's view, appears to violate both assumptions. The two models that include a polling measure on the Clinton v. Trump race both forecast a narrow Clinton victory. In contrast, Helmut Norpoth, using only a single predictor — the two nominees relative performance in the New Hampshire and South Carolina primaries) — forecasts a high likelihood of a comfortable Trump victory while Fair's model predicts a near landslide Trump victory. In fact, Norpoth recently suggested, without the modesty usually associated with academic modeling, that a Trump victory is "a virtual certainty."

Note that all of these models forecast the presidential election based on the winner of the national two-party vote, and do not factor in third-party candidates. And they assume that a majority or plurality of the popular vote will produce the 270 electoral votes needed for victory. Those are reasonable assumptions based on the historical record but, as William Howard Taft and Al Gore would testify, not foolproof.

Data-Intensive, Continuous Polling

Another approach to forecasting is to estimate the electoral vote outcome directly, by using sophisticated statistical analyses of mostly state and national trial-heat polls conducted continuously throughout the general election campaign. Since 2004 biophysicist Sam Wang has conducted a meta-analysis of state presidential polls to provide more accurate snapshots of the race for a majority in the Electoral College. His Princeton Election Consortium (PEC) blog hosts reports on his forecasting model, which beginning in 2012 added specific predictions. Nate Silver of FiveThirtyEight was a pioneer in this development. He initially forecast the 2008 presidential election. His blog became an essential resource for election watchers and remains so today. When Silver moved from The New York Times to ESPN in 2013, The Times under Josh Katz developed its own polling-based forecasting model as part of The Upshot platform. Finally, statistician Drew Linzer, who has written the most comprehensive scholarly case for his state-based forecasting model, introduced his Votamatic site for the 2012 election. Linzer’s model became part of Daily Kos website in 2016.

The Upshot conveniently provides daily updates from the four models of the probability each attaches to the predicted winner of the presidential election nationally and in each of the fifty states. As this blog was written, all four predicted a Clinton victory with probabilities ranging from 67 to 90 percent; the three reported electoral vote forecasts range from 298 to 324. Clinton has maintained a consistent lead in all of the models since midyear, although the size of her lead and the likelihood of her victory has fluctuated, more in some than in others.

Understanding The Models

Detailed descriptions of each model are provided on the individual sites. The models are similar in a number of respects. They all use state polls and then statistically adjust them to deal with outliers and to reflect recent trends. They also use past election polling data to improve the accuracy of their use of current polls. Three use simulation techniques to estimate the probability of state election outcomes; PEC uses a measure of the median state poll. Three of the models use polls collected by HuffPost Pollster; FiveThirtyEight aggregates state and national polls itself.

But the models also differ in a variety of respects. For example, what polls to include; whether some polls are discounted on grounds of quality or House effects; whether and how to factor in any measure of the fundamentals of the current cycle and past election results; the details of the statistical operations; and what information is made available publicly. FiveThirtyEight provides the results of three forecasting models: its default polls-only forecast, a polls-plus forecast that includes economic and historical data, and a now-cast forecast, presenting the likelihood of a candidate winning today. The polls-plus is the most stable over the course of the campaign but the three models are expected to converge as we get closer to the election. Today Clinton’s odds of victory range from 66 to 68 percent across the three FiveThirtyEight models, about the same as they were in June.

I mentioned above that HuffPost Pollster provided the polling data for most of these state-based forecasting models. Real Clear Politics also compiles publicly available national and state polls and reports simple averages of recent ones. Pollster applies its own criteria in deciding which polls to include and then calculates poll 'averages' differently by using a statistical smoothing technique involving many simulations to build trend lines into the estimates of national and state polls to reduce the 'noise,' mostly the impact of outliers. Three of the forecasting models (not including PEC) use a similar technique. FiveThirtyEight makes additional adjustments in these estimates. All of which reminds us that where the race for the national and state popular vote stands at any point in time is not a known quantity but a number of approximations based on different aggregating procedures. To the extent these estimates remain stable or move in the same direction, we can be more confident. At the very least, polling 'averages' are more reliable than individual polls.

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