In a Markov decision problem with hidden state variables, a posterior distribution serves as a state variable and Bayes' law under an approximating model gives its law of motion. A decision maker expresses fear that his model is misspecified by surrounding it with a set of alternatives that are...

We examine optimal and other monetary policies in a linear-quadratic setup with a relatively general form of model uncertainty, so-called Markov jump-linear-quadratic systems extended to include forward-looking variables. The form of model uncertainty our framework encompasses includes: simple...

The literature applying information-theoretic ideas to economics has so far considered only Gaussian uncertainty. Ex post Gaussian uncertainty can be justified as optimal when the associated optimization problem is linear-quadratic, but the literature has often assumed Gaussian uncertainty even...

This paper presents an estimated DSGE model for the European Monetary Union. Our approach, contrary to the previous studies, accounts for heterogeneity within the euro area. We advance the empirical literature by estimating an open-economy model with unfiltered data, which is a much more...

We analyze the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration. We show that combining two time scales for...