As Gingrich’s fate rises, so does Obama’s

As he prepares for his third State of the Union address--and, he hopes, not his last--Barack Obama's likelihood of reelection has soared in the last few days to 56.8 percent, the highest it has been since last July. This movement correlates with Newt Gingrich's increased likelihood of gaining the Republican nomination, now at 29.7 percent, up from about 5 percent. This upward trend also correlates with a simultaneous downward movement of Mitt Romney's likelihood of winning the presidency if he wins the nomination, now at 44.0, down from about 48 percent. We utilize prediction market data for these likelihoods.

Sources: Betfair and Intrade

In short, the markets think Obama is more likely to defeat Gingrich than Romney, so when the former speaker's fortunes elevate, so do the president's. Over the last week, Gingrich's likelihood of winning the nomination has climbed from about 5 percent to about 30 percent. Currently, Gingrich is about 39 percent likely to defeat Obama if he makes it to the general election, while Romney is about 44 percent likely to reach the White House if he's the nominee.

An ordinary least squares regression--one of the most weathered tools in the statistician's toolbelt--determines that the Gingrich-Romney battle determines about 87.5 percent of the variability in Obama's likelihood of reelection. To wit, for every 10 percent more likely Gingrich is to win the nomination, Obama is 0.75 percent more likely to win reelection. For every 10 percent less likely Romney is to win the election if he wins the nomination, Obama is 2.75 percent more likely to win reelection. If they're watching the same markets we are at 1600 Pennsylvania, you can be sure they're wearing Gingrich pom-poms.

Follow along on PredictWise for the real-time likelihood of the upcoming republican primaries, the Republican nomination, and the presidential election.

David Rothschild is an economist at Yahoo! Research. He has a Ph.D. in applied economics from the Wharton School of Business at the University of Pennsylvania. His dissertation is in creating aggregated forecasts from individual-level information. Follow him on Twitter @DavMicRot and email him at

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