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Christopher Sims and Thomas Sargent are the newest winners of the Nobel Prize in Economics.

I have heard  and read about both of these guys for years, but I did not really know about their contributions until reading this article.

Apparently, they had much to do with the concept of rational expectations, and the role that expectations play in the influence of monetary policy.

They won their Nobel for “their empirical research on cause and effect in the macroeconomy,” in the academy’s words. What that means, in part, is that they have done some serious math. Today, ideas they largely formed in the 1970s and ’80s help shape the thinking inside the Fed and on Wall Street.

Their work goes beyond old labels like Keynesianism and the monetarism of Milton Friedman. They have shown that fiscal and monetary policy are inextricably linked, and their research reflects the broad shift in economics from words to numbers — toward a level of empirical analysis that few outside the profession can readily grasp. But it contains a kernel of skepticism appropriate for these troubled times. In a world of uncertainty and constraint, cause and effect may not be what they seem. As a result, we must test and retest our assumptions — and try to prepare for the unexpected.

“The most impressive thing about them as scholars,” says David Easley, an economist at Cornell University, “is that in recent years they have questioned the assumptions of the models they helped to create, and they have been at the vanguard of the efforts to go beyond them.”

This last paragraph is interesting to me. They agree that there is room for new ideas and models that might better predict the results of economic policy, something our new nobel laureates admit is still not done very well.

Mr. Sargent is tough on himself, saying the “rational expectations approach” and the techniques he has helped to pioneer don’t yet capture economic reality. How do people really think, as individuals and in a market? How should we account for changes in expectations as people learn? How should we incorporate human thinking more realistically into economic models? He’s grappling with such questions, seeking more sophisticated techniques that incorporate what he calls the theory of “adaptive learning.”

His own assumptions need to be continually re-examined “to capture a fundamentally uncertain, constrained, complicated world,” he says.

Simon Potter, director of economic research at the New York Federal Reserve, says he has taken Mr. Sargent’s message to heart: “Our profession hasn’t reached the stage where it can reliably forecast the economy,” Mr. Potter says. “Our collective failure to do so in the financial crisis shows this.”

Maybe the next Nobel goes to a newer model that solves some of those problems. Any volunteers?