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Finance and Economics Discussion Series
Finance and Economics Discussion Series logo links to FEDS home page Solving Linear Rational Expectations Models: A Horse Race
Gary S. Anderson

Abstract: 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), (Klein, 1999), and (Uhlig, 1999). While all six prcedures yield similar results for models with a unique stationary solution, the AIM algorithm of (Anderson and Moore, 1983) provides the highest accuracy; furthermore, this procedure exhibits significant gains in computational efficiency for larger-scale models.

Keywords: Linear Rational Expectations, Blanchard-Kahn, Saddle Point Solution.

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Last update: June 14, 2006