When models break down

Why Helmut Norpoth’s election forecast is so fraught with errors

Confirmation bias is a hell of a phenomenon. This search for confirmatory evidence—or even the tendency to warp facts into confirmatory evidence—is even stronger when one has staked her professional reputation on the high-profile successes (and failures) of their work. And confirmation bias is the best explanation I can think of to explain why Helmut Norpoth, an old-timer in election forecasting, political scientist at Stony Brook and I presume otherwise intelligent person, proclaims that Donald Trump has a 91-95% chance of winning the 2020 presidential election.

To some extent, I can’t even believe I have to write up this post. The model Norpoth is relying on for such claims (which he calls “The Primary Model”) is so bad that I had guessed most reasonable people would rightly reject it out of hand. But it turns out that most people are not experts in election forecasting, and many others aren’t reasonable political analysts—or, if they, are Norpoth has duped them.

Put simply, The Prima…