In the CNN/ORC poll (see Q13), 42% of respondents said they were “more likely to support Trump,” and 44% said “less likely.” That’s a net difference of negative 2 percent, which is worse than any value in the graph above. By that measure, the Republican convention was a failure.
In both graphs, a notable shift occurred around the time that national elections became more polarized, in 2000. We are in an era of government shutdowns, endless Congressional investigative hearings,
criminalization of political opposition, and ever-more-contentious judicial nominations. Voter entrenchment appears to be just one more symptom.
In the coming week you may be surprised to see relatively little change in the Princeton Election Consortium electoral-vote tracker and November win probability. There are two reasons: (1) We use state polls, which take time to reflect national shifts. (2) The Bayesian-win probability listed in the banner uses polls over the entire 2016 campaign to set a prior expectation for where things are likely to head. The second assumption also has the more traditional name of “
regression to the mean.” Effectively, these two mechanisms prevent the calculations from spinning out of countrol whenever there is a momentary bump in polling. Therefore, today’s November win probability is 80%.
Of course, if the race shifts in a lasting manner, it will show up eventually. Just to state the obvious, now is not the optimal time to gauge where the race is headed in steady state. Recall that in 2008, the Republican convention and the addition of Sarah Palin to the ticket led the race to
briefly appear tied.
If you want to see the prediction without the Bayesian prior, the assumption that polls can drift equally in either direction, toward Clinton or toward Trump, is therandom drift probability. Today, that probability is 65%.
