This paper describes a set of algorithms for quickly and reliably solving linear rational expectations models. The utility, reliability and speed of these algorithms are a consequence of 1) the algorithm for computing the minimal dimension state space transition matrix for models with arbitrary...

Of the many studies analyzing the Federal Reserve's post-October 6, 1979 nonborrowed reserve (NBR) operating procedure, none has focused on weekly money market dynamics under rational expectations. This paper employs the rational expectations assumption in an explicit institutional model of the...

This paper compares the functionality, accuracy, computational efficiency, and practicalities of alternative approaches to solving linear rational expectations models, including the procedures of (Sims, 1996), (Anderson and Moore, 1983), (Binder and Pesaran, 1994), (King and Watson, 1998),...

We present an algorithm and software routines for computing nth order Taylor series approximate solutions to dynamic, discrete-time rational expectations models around a nonstochastic steady state. The primary advantage of higher-order (as opposed to first- or second-order) approximations is...