Klein (2000) advocates the use of the Schur decomposition of a matrix pencil to solve linear rational expectations (RE) models. Meanwhile his algorithm has become a center piece in several computer codes that provide approximate solutions to (non-linear) dynamic stochastic general equilibrium...

A solution method is derived in this paper for solving a system of linear rational-expectations equation with lagged expectations (e.g., models incorporating sticky information) using the method of undetermined coefficients for the infinite MA representation. The method applies a combination of...

This paper has developed a solution algorithm for linear rational expectation models under imperfect information. Imperfect information in this paper means that some decision makings are based on smaller information sets than others. The algorithm generates the solution in the form of k_t+1 =...

Linear models with infinite horizon generally admit infinitely many rational expectations solutions. Consequently, some additional selection devices are needed to narrow the set of relevant solutions. The viewpoint of this paper is that a solution will be more likely to arise if it is locally...

This paper has developed a solution algorithm for linear rational expectation models under imperfect information. Imperfect information in this paper means that some decision makings are based on smaller information sets than others. The algorithm generates the solution in the form of k_t+1 =...