For those who diss Krugman and love Cal Thomas (which is to say, almost everybody that reads my local paper).
And don't let anybody tell you partisanship doesn't matter in accuracy, or that lawyers know what they're talking about.
In this paper, we report on the first-ever test of the accuracy of predictions in the media. We sampled the predictions of 26 individuals who wrote columns in major newspapers and/or appeared on the three major Sunday television news shows (Face the Nation, Meet the Press, and This Week) over a 16 month period from September 2007 to December 2008. Collectively, we called these pundits and politicians “prognosticators.” We evaluated each of the 472 predictions we recorded, testing its accuracy. Based on an analysis of these predictions, we answer three questions:

1. Which pundits are most accurate? We found wide disparities in the predictive accuracy of these individuals, and we divided them into “the good, the bad, and the ugly.”

2. Which characteristics are associated with predictive accuracy? We examined the effects of age, education, ideology, and other factors on accuracy.

3. What is the purpose of media pundits? We discuss whether the ordinary citizen should look to pundits for deeper analysis of events, or whether pundits are simply a more enjoyable way to learn about the events of the day. We also consider alternative viewpoints, including the notion that pundits are useful as representatives of opposing points of view in the country, and the idea that they are simply entertainers.
The most accurate prognosticator was Paul Krugman of The New York Times and Princeton University, followed by Maureen Dowd, another columnist for the Times, and former Pennsylvania governor Ed Rendell. The worst prognosticator was Cal Thomas, a syndicated columnist. South Carolina Senator Lindsay Graham was next worst, and Michigan Senator Carl Levin was third worst.

We discovered that a few factors impacted a prediction's accuracy. The first is whether or not the prediction is a conditional; conditional predictions were more likely to not come true. The second was partisanship; liberals were more likely than conservatives to predict correctly. The final significant factor in a prediction's outcome was having a law degree; lawyers predicted incorrectly more often. Partisanship had an impact on predictions even when removing political predictions about the Presidential, Vice Presidential, House, and Senate elections.