Time‐varying parameters and state space models

Timo Teräsvirta, Dag Tjøstheim and W. J. Granger

in Modelling Nonlinear Economic Time Series

Published in print December 2010 | ISBN: 9780199587148
Published online May 2011 | e-ISBN: 9780191595387 | DOI:

Series: Advanced Texts in Econometrics

Time‐varying parameters and state space models

More Like This

Show all results sharing this subject:

  • Econometrics and Mathematical Economics


Show Summary Details


Linear state space models have become popular in time series, and there are applications to many fields. The Kalman filter is often a fundamental tool. In this chapter it is shown that there are extensions of these concepts to a nonlinear framework through such devices as the extended Kalman filter and particle filters. Hidden Markov chains represents an alternative but related technique, where parameters are replaced by stochastic processes; i.e., Markov chains. The chapter also contains a short section on estimating these types of models.

Keywords: state space; Kalman filter; particle filter; hidden Markov chains

Chapter.  17138 words. 

Subjects: Econometrics and Mathematical Economics

Full text: subscription required

How to subscribe Recommend to my Librarian

Buy this work at Oxford University Press »

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.