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Higher-order perturbation solutions to dynamic, discrete-time rational expectations models Author info | Abstract | Publisher info | Download info | Related research | Statistics Eric Swanson
Gary Anderson
Andrew Levin
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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.
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Paper provided by Federal Reserve Bank of San Francisco in its series Working Paper Series with number
2006-01.
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Date of creation: 2006Date of revision:
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Keywords: Macroeconomics - Econometric models ; Business cycles ; Monetary policy ; Other versions of this item:
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.: Kollmann, Robert, 2002.
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