Higher-order perturbation solutions to dynamic, discrete-time rational expectations models
AbstractWe 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.
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Bibliographic InfoPaper provided by Federal Reserve Bank of San Francisco in its series Working Paper Series with number 2006-01.
Date of creation: 2006
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-03-18 (All new papers)
- NEP-CMP-2006-03-18 (Computational Economics)
- NEP-DGE-2006-03-18 (Dynamic General Equilibrium)
- NEP-MAC-2006-03-18 (Macroeconomics)
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