Abstract:
Based on the axiomatic framework of Choquet decision theory, we develop a
closed-form model of Bayesian learning with ambiguous beliefs about the mean
of a normal distribution. In contrast to rational models of Bayesian learning the
resulting Choquet Bayesian estimator results in a long-run bias that reflects the
agent’s ambiguity attitudes. By calibrating the standard equilibrium conditions
of the consumption based asset pricing model we illustrate that our approach
contributes towards a resolution of the risk-free rate puzzle. For a plausible parameterization
we obtain a risk-free rate in the range of 35 −5%. This is 1 −25%
closer to the empirical risk-free rate than according calibrations of the rational
expectations model.