How Statisticians Won the Battle And Mood Won the War
By Robert Folsom | November 7, 2012
In the late stages of the 2012 presidential campaign, one of the loudest sideshows was the debate over whether polls accurately predict election outcomes.
The debate pitted data crunchers like 538’s Nate Silver and neuroscientist Sam Wang of the Princeton Election Consortium against critiques like “nobody knows anything” from Peggy Noonan and “you can only measure what matters least” from Michael Gerson.
Now that the numbers have been counted, it’s fair to say that the results landed firmly on the side of the statisticians. For example, Silver’s election-eve analysis proved stunningly accurate.
Yet in January 2012, four researchers published an even more stunning statistical forecast. Their research identified the collective influence that “regulates voting with respect to the re-election or rejection of incumbents.”
What’s more, this forecast has nothing to do with asking voters what they were going to do, or had just done. The research debuted in the paper titled,
Social Mood, Stock Market Performance and US Presidential Elections:
A Socionomic Perspective on Voting Results
This was no sideshow about statistical models; the paper identified the main performer in the center ring.
The elections paper did of course meet all the standards of quality scholarship. It posted in January on the Social Science Research Network (SSRN) website, home to some 350,000 research papers. Yet in just 10 months the elections paper became one of its most-downloaded papers ever.
And as I mentioned recently on this page, the elections paper has now been published in Sage Open, a peer-reviewed journal of the social and behavioral sciences.
But most importantly: While observers express surprise at the “landslide” electoral college result, NO ONE who read this paper was surprised by the outcome of the 2012 presidential election. That’s because it explained when incumbent presidents are — and are not — reelected to a second term.
And yes, the election paper also explains why.
If you haven’t read it, please know that it’s still available as a free download from SSRN. Follow this link – you owe it to yourself.