A New Approach to Drawing States in State Space Models

We introduce a new method for drawing state variables in Gaussian state space models from their conditional distribution given parameters and observations. Unlike standard methods, our method does not involve Kalman filtering. We show that for some important cases, our method is computationally more efficient than standard methods in the literature. We consider two applications of our method.

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Year of publication:	2007
Authors:	McCAUSLAND, William J. ; MILLER, Shirley ; PELLETIER, Denis
Institutions:	Centre Interuniversitaire de Recherche en Économie Quantitative (CIREQ)
Subject:	State space models \| Stochastic volatility \| Count data

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Extent:	application/pdf
Series:	Cahiers de recherche.
Type of publication:	Book / Working Paper
Notes:	26 pages
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008617027