There is only one person who correctly forecast the U.S. presidential election of 2016. His name is not Nate Silver or Sam Wang or Nate Cohn. It is Donald Trump. Trump made a mockery of the predictions of all the erudite analytical election forecast modelers. Uttering the battle cry of “Brexit Plus,” he confidently grabbed the thin sliver of a chance that the models gave him by winning the Sun Belt states of Florida and North Carolina and then, in a near-miraculous example of threading the needle, flipping not just one but three of the ordinarily blue Rust Belt states that formed Hillary Clinton’s “firewall” — Wisconsin, Michigan and Pennsylvania — to red.
Like everyone else, I am stunned. In my pre-election Abstractions post below, I commented that the “science of election modeling still has a long way to go,” but I must admit that the distance is far beyond what I had imagined. It seems pointless now to try to dissect the statewide predictions of the various models as I had promised to do — none of them were even remotely in the ballpark. It is unclear how long it will take before election forecasting is trusted again.