Computing Second-Order-Accurate Solutions for Rational Expectation Models Using Linear Solution Methods

Abstract

This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. This result is a state-space representation for the realized values of the variables of the model. This state-space representation can easily be used to compute impulse responses as well as conditional and unconditional forecasts.Second-order approximation; solution method for rational expectation models.