done better over the same period. This theory makes several distinctive predictions, which, for concreteness, we develop in … a stock-market setting. For example, starting with symmetric and homoskedastic fundamentals, the theory yields …

We study the design of optimal monetary policy under uncertainty in a dynamic stochastic general equilibrium models. We … use a Markov jump-linear-quadratic (MJLQ) approach to study policy design, approximating the uncertainty by different … a benchmark New Keynesian model, analyzing how policy is affected by uncertainty, and how learning and active …

choice theory under uncertainty to explore the ramifications of model uncertainty and learning in environments in which … decision theory to characterize when learning or discriminating among competing probability models is challenging. I also use …

-looking models; time-varying central-bank judgment about the state of model uncertainty; and so forth. We provide an algorithm for … uncertainty, so-called Markov jump-linear-quadratic systems extended to include forward-looking variables. The form of model … uncertainty our framework encompasses includes: simple i.i.d. model deviations; serially correlated model deviations; estimable …