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

Bayesian Estimation of DSGE Models

Edward P. Herbst and Frank Schorfheide


Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood ... More

Keywords: dynamic stochastic general equilibrium, DSGE models, macroeconomics, policy analysis, central bank, Bayesian analysis, Monte Carlo method, algorithm, computation

Bibliographic Information

Print publication date: 2015 Print ISBN-13: 9780691161082
Published to Princeton Scholarship Online: October 2017 DOI:10.23943/princeton/9780691161082.001.0001


Affiliations are at time of print publication.

Edward P. Herbst, author
Federal Reserve Board

Frank Schorfheide, author
University of Pennsylvania