Higher-order perturbation solutions to dynamic, discrete-time rational expectations models

Gary Anderson, Andrew Levin () and Eric T. Swanson

No 2006-01, Working Paper Series from Federal Reserve Bank of San Francisco

Abstract: 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 that they are valid not just locally, but often globally (i.e., over nonlocal, possibly very large compact sets) in a rigorous sense that we specify. We apply our routines to compute first- through seventh-order approximate solutions to two standard macroeconomic models, a stochastic growth model and a life-cycle consumption model, and discuss the quality and global properties of these solutions.

Keywords: Macroeconomics - Econometric models; Business cycles; Monetary policy (search for similar items in EconPapers)
Date: 2006
New Economics Papers: this item is included in nep-cmp, nep-dge and nep-mac
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