Think of it another way: How much attention should be paid to a forecaster or investment model that claimed to foretell market and economic cycles, yet completely missed the 2008-09 crash? You might take a look, but with knowledge of that huge oversight, you would probably give it little weight.
To be fair, the Sommer article does quote Fair as saying that his model may well be wrong about this coming election too: “Each election has weird things in it, yet the model usually works pretty well . . . This year, though, I don’t know. This year really could be different.”
Let’s look more closely at the process underlying the model.
After the 2012 election flub, the Wall Street Journal’s Justin Lahart wrote that:
The model relies on just three pieces of information: The per capita growth rate of gross domestic product in the three quarters before the election, inflation over the entire presidential term and the number of quarters during the term when GDP per capita growth exceeded 3.2%.
Plug those data points into Mr. Fair’s model, and it says that Mr. Romney should have taken 51% of the two party vote to President Obama’s 49%. Instead, it looks like it was 51.3% for President Obama to Mr. Romney’s 48.7%. It was only the third time since 1916 that the model failed to predict the popular-vote winner.
It's easy to see the problems here:
Fair's model focuses on the popular vote while ignoring the Electoral College, which determines who wins the election; The information it relies upon, especially gross domestic product and inflation, are volatile, often unreliable in the short term and subject to substantial revision; The model seems to have been developed to use information that would have successfully predicted past elections; it seems almost trite to say it, but the past is, of course, no guarantee of future results; We can't tell if the model's track record was the result of random good fortune or not.
The narrative that was common in the mainstream press during the 2012 presidential election campaign was that it was a very tight race, and the outcome would be close; it wasn't. Meanwhile, other modelers did better; neuroscientist Sam Wang of Princeton precisely nailed the 2012 election, and Nate Silver, of 538, had it mostly right. Though they were both on target, we should be cautious about whether these models were really better or just happened to come up with the correct result.
For investors, the lessons are clear: Don't put too much stock in models that can't stand the test of time, are oversimplified and may be random in their outcomes.
Barry Ritholtz started the Big Picture blog in 2003 and is the founder of Ritholtz Wealth Management, an asset management and financial planning firm.