In this paper we present a method for using rational expectations in a linear-quadratic optimizationframework. Following the approach put forward by Sims, we solve the model through a QZdecomposition, which is generally easier to implement than the more widely used method of Blanchardand Kahn.

We present a computationally effective method of solving regular linear dynamic systems based on Schur decomposition. One of the advantage of presented method is possibility of problem dimension reduction. This allows for efficient solution of models with very large set of endogenous variables...