Empirical Rationality in the Stock Market

Rational expectations models make stringent assumptions on the agent’s knowledge about the true model. This paper introduces a model in which the rational agent realizes that using a given model involves approximation errors, and adjusts behavior accordingly. If the researcher accounts for this empirical rationality on part of the agent, the resulting empirical model assigns likelihood to the data actually observed, unlike in the unmodified rational expectations case. A Lucas (1978)-type asset pricing model which incorporates empirical rationality is constructed and estimated using U.S. stock data. The equilibrium asset pricing function is seriously affected by the existence of approximation errors and the descriptive properties and normative implications of the model are significantly improved. This suggests that investors do not — and should not — ignore approximation errors.