Equilibrium Modeling of Asset Prices: Rationality Versus Rules of Thumb

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Abstract
General equilibrium models with representative agents have proved to be inadequate descriptions of U.S. financial data. I present a model with heterogeneous agents, optimizers, and nonoptimizers that exhibits high stock-price volatility and mimics empirical regularities found in U.S. consumption, stock return, and three-month treasury-bill return data. The simulation and estimation of the model are performed using a new technique called “backsolving,” which is of independent interest to researchers attempting to solve nonlinear, stochastic models.