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Higher-Order Perturbation Solutions to Dynamic, Discrete-Time Rational Expectations Models: Methods and an Application to Optimal Monetary Policy

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Author Info
Eric Swanson
Gary Anderson
Andrew Levin

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Abstract

We present an algorithm and software routines for computing nth-order approximate solutions to dynamic, discrete-time rational expectations models around a nonstochastic steady state. We apply these routines to investigate the optimal monetary policy with commitment in an optimizing-agent model with nominal price rigidities, subject to a fiscal policy that is stochastic, suboptimal, and exogenous to the central bank

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Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 146.

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Date of creation: 11 Nov 2005
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Handle: RePEc:sce:scecf5:146

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Web page: http://comp-econ.org/
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Related research
Keywords: perturbation methods Mathematica nth order optimal monetary policy

Find related papers by JEL classification:
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

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This page was last updated on 2008-8-5.

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