patrick.net

NAte explains why his model gives Trump such a high chance of winning (approximately 15%).

http://fivethirtyeight.com/features/election-update-why-our-model-is-more-bullish-than-others-on-trump/

Assumption No. 4: State outcomes are highly correlated with one another, so polling errors in one state are likely to be replicated in other, similar states.

In 2012, Obama beat his polling by 2 or 3 percentage points in almost every swing state. The same was true in 1980 when Ronald Reagan won in a landslide — instead of the modest lead that polls showed a few days before the election — and claimed 489 electoral votes by winning almost every competitive state. You also frequently see this in midterms — Republicans beat their polling in almost every key Senate and gubernatorial race in 2014, for example.

Basically, this means that you shouldn’t count on states to behave independently of one another, especially if they’re demographically similar. If Clinton loses Pennsylvania despite having a big lead in the polls there, for instance, she might also have problems in Michigan, North Carolina and other swing states. What seems like an impregnable firewall in the Electoral College may begin to collapse.

What if we changed this assumption? If we assumed that states had the same overall error as in the FiveThirtyEight polls-only model but that the error in each state was independent, Clinton’s chances would be … 99.8 percent, and Trump’s chances just 0.2 percent. So assumptions about the correlation between states make a huge difference.