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Higher order approximations of stochastic rational expectations models

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Author Info
Kowal, Pawel

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Abstract

We describe algorithm to find higher order approximations of stochastic rational expectations models near the deterministic steady state. Using matrix representation of function derivatives instead of tensor representation we obtain simple expressions of matrix equations determining higher order terms.

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File URL: http://mpra.ub.uni-muenchen.de/3913/
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 3913.

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Date of creation: Jul 2007
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Handle: RePEc:pra:mprapa:3913

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Related research
Keywords: perturbation method DSGE models

Find related papers by JEL classification:
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation

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This page was last updated on 2008-7-26.

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