Predicting financial crises with agent-based models

Nature complains in an editorial that standard economic models failed to predict the recent financial crisis and endorses the idea that agent-based models, which detail the behavior of individual consumers, producers, investors and other agents, may be more useful. J. Doyne Farmer and Duncan Foley further explore the idea in the same issue (The economy needs agent-based modelling).

Such models do not rely on the assumption that the economy will move towards a predetermined equilibrium state, as other models do. Instead, at any given time, each agent acts according to its current situation, the state of the world around it and the rules governing its behaviour. An individual consumer, for example, might decide whether to save or spend based on the rate of inflation, his or her current optimism about the future, and behavioural rules deduced from psychology experiments. The computer keeps track of the many agent interactions, to see what happens over time.

I wonder how agent-based models would model the behavior of agents that use agent-based models to guide their decisions. Well, no need to wonder. Given that all agents can and do use at least as much information as models there is no way for models to outsmart the system. Financial crises are inherently unpredictable. And this is precisely what standard economic models say.