Sequential Action and Beliefs Under Partially Observable DSGE Environments

This paper introduces a classification of DSGEs from a Markovian perspective, and positions the class of Partially Observable Markov Decision Process (POMDP) to the center of a generalization of linear rational expectations models. The analysis of the POMDP class builds on the previous development in dynamic controls for linear system, and derives a solution algorithm by formulating an equilibrium as a fixed point of an operator that maps what we observe into what we believe. Copyright Springer Science+Business Media New York 2012