Higher order approximations of stochastic rational expectations models

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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Year of publication:	2007-07
Authors:	Kowal, Pawel
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	perturbation method \| DSGE models

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C63 - Computational Techniques ; C61 - Optimization Techniques; Programming Models; Dynamic Analysis ; E17 - Forecasting and Simulation
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005616850