Mr. Farmer sees a perhaps greater flaw in the models' mathematical structure. A typical "dynamic stochastic general equilibrium" model-so called for its efforts to incorporate time and random change-consists of anywhere from a few to dozens of interlinked equations, which must agree before the model can spit out a solution. If the equations get too complex, or if there are too many elements, the models have a hard time finding the point at which all the players' preferences meet.

To keep things simple, economists leave out large chunks of reality. Before the crisis, most models didn't have banks, defaults or capital markets, a fact that proved problematic when the financial crisis hit. They tend to include only households, firms, central banks and the government. They also commonly use a single equation to represent each player, impairing the models' ability to explain the unexpected outcomes that can emerge when millions of different people interact.

"You are limited by what you can solve," says Mr. Farmer. "It puts the whole enterprise in a straitjacket."

His proposal: Create a richly complex, computer-based simulation of the economy like those scientists use to model weather patterns, epidemics and traffic. Given enough computing power, such "agent-based" models can include millions of individual players, who don't have to be rational or agree with one another. Instead of equations that must be solved, the players have open-ended rules of behavior, such as, "If I've just turned 55 and I'm feeling blue, I'll buy a sports car."

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