Solving linear rational expectations models: a horse race

Gary Anderson

No 2006-26, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

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 procedures 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: Rational expectations (Economic theory); Econometric models (search for similar items in EconPapers)
Date: 2006
New Economics Papers: this item is included in nep-cba, nep-cmp and nep-ecm
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Citations: View citations in EconPapers (13)

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Related works:
Journal Article: Solving Linear Rational Expectations Models: A Horse Race (2008)
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