Higher-order perturbation solutions to dynamic, discrete-time rational expectations models
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.
File(s): File format is application/pdf http://www.frbsf.org/publications/economics/papers/2006/wp06-01bk.pdf
Provider: Federal Reserve Bank of San Francisco
Part of Series: Working Paper Series
Publication Date: 2006