Perturbation Methods for Markov-Switching Models

Tao Zha, Juan F Rubio-Ramirez, Daniel Waggoner and Andrew Foerster

No 239, 2010 Meeting Papers from Society for Economic Dynamics

Abstract: This paper develops a methodology for approximating rational expectations models with Markov Switching. Specifically, we consider how to do both linear and higher-order approximations, including cases when each individual regime is associated with it's own steady state. We document the importance of using higher-order approximations in economies that have parameter switching that affects variances. We illustrate our algorithm by considering a standard real business cycle economy with Markov switching in total factor productivity drift and variance and assess the accuracy of our approximations. Our method allows for further empirical analysis of economies with Markov switching.

Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (8)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models (2016)
Working Paper: Perturbation Methods for Markov-Switching DSGE Models (2014)
Working Paper: Perturbation Methods for Markov-Switching DSGE Models (2013)
Working Paper: Perturbation Methods for Markov-Switching DSGE Models (2013)
Working Paper: Perturbation methods for Markov-switching DSGE models (2013)
Working Paper: Perturbation methods for Markov-switching DSGE model (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:red:sed010:239

Access Statistics for this paper

More papers in 2010 Meeting Papers from Society for Economic Dynamics Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christian Zimmermann ().