Higher-Order Perturbation Solutions to Dynamic, Discrete-Time Rational Expectations Models
Federal Reserve Bank of San Francisco Working Paper Series 2006-01
31 Pages Posted: 24 Jul 2007
Date Written: January 2006
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: Business cycles, Macroeconomics, Monetary policy, Econometric models
JEL Classification: C61, C63, E37
Suggested Citation: Suggested Citation
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