Jump to ContentJump to Main Navigation
Bayesian Estimation of DSGE Models$
Users without a subscription are not able to see the full content.

Edward P. Herbst and Frank Schorfheide

Print publication date: 2015

Print ISBN-13: 9780691161082

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691161082.001.0001

Show Summary Details
Page of

PRINTED FROM PRINCETON SCHOLARSHIP ONLINE (www.princeton.universitypressscholarship.com). (c) Copyright Princeton University Press, 2022. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in PRSO for personal use.date: 17 May 2022

Particle Filters

Particle Filters

(p.171) Chapter 8 Particle Filters
Bayesian Estimation of DSGE Models

Edward P. Herbst

Frank Schorfheide

Princeton University Press

This chapter explains how the key difficulty that arises when the Bayesian estimation of DSGE models is extended from linear to nonlinear models is the evaluation of the likelihood function, and focuses on the use of particle filters to accomplish this task. The basic bootstrap particle filtering algorithm is remarkably straightforward, but may perform quite poorly in practice. Thus, much of the literature about particle filters focuses on refinements of the bootstrap filter that increases the efficiency of the algorithm. The accuracy of the particle filter can be improved by choosing other proposal distributions. While the tailoring (or adaption) of the proposal distributions tends to require additional computations, the number of particles can often be reduced drastically, which leads to an improvement in efficiency.

Keywords:   particle filters, DSGE models, Bayesian estimation, bootstrap filter, proposal distributions, filtering algorithm

Princeton Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us.