Faculty of Economics and Business Administration Publications Database

Biased Bayesian learning with an application to the risk-free rate puzzle

Zimper, Alexander
Volume: 39
Pages: 79 - 97
Month: February
ISSN-Print: 0165-1889
Link External Source: Online Version
Year: 2014
Keywords: Ambiguity; Non-additive probability measures; Bayesian learning; Truncated normal distribution; Risk-free rate puzzle

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 3.5–5%. This is 1–2.5% closer to the empirical risk-free rate than according calibrations of the rational expectations model.