Abstract
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.
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Kim, SH. Sequential Action and Beliefs Under Partially Observable DSGE Environments. Comput Econ 40, 219–244 (2012). https://doi.org/10.1007/s10614-012-9323-1
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DOI: https://doi.org/10.1007/s10614-012-9323-1