Learning Within Rational-Expectations Equilibrium
Models of macroeconomic learning are populated by agents who possess a great deal of knowledge of the "true" structure of the economy, and yet ignore the impact of their own learning on that structure; they may learn about an equilibrium, but they do not learn within it. An alternative learning model is presented where agents' decisions are informed by hypotheses they hold regarding the economy. They periodically test these hypotheses against observed data, and replace them if they fail. It is shown that agents who learn in this way spend almost all of the time approximating rational-expectations equilibria.
|Date of creation:||01 Jan 2012|
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- John Nachbar, 2010. "Prediction, Optimization and Learning in Repeated Games," Levine's Working Paper Archive 576, David K. Levine.
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