The November outcome should be within 1 SD of current polls approximately two-thirds of the time. Hillary Clinton’s polling margin over Donald Trump is currently +8% (median of 19 pollsters since mid-March) – twice the standard deviation. Based on past years, how likely is it that Trump can catch up? It is possible to convert Clinton’s lead to a probability using the t-distribution*, which can account for outlier events like 1964 and 1980. Using this approach, the probability that Trump can catch up by November is 9%, and the probability that Clinton will remain ahead of Trump is 91%**. This probability doesn’t take into account Electoral College mechanisms. But since the bias of the Electoral College is quite small, it does not make a difference in the calculation.
I should note that the polls have been telling us this information for some time. In the first half of March, Clinton led Trump by a median of 9 percentage points. Using an SD of 4.5 percentage points, her win probability would come out as 93%. So today’s estimate has been knowable for several months.
This is a result that may excite Democrats. However, it is subject to change. For example, the SD increases to about 7% in June, which combined with a lead of Clinton +8% corresponds to an 83% win probability, less certain than today. And of course the polls could change. I don’t know why polls would be less predictive in summer. Maybe general election campaign events drive polls away from where they would naturally go otherwise. Post-convention bounces would be examples of such events.
