Franklin

Bayesian Estimation of DSGE Models / Frank Schorfheide, Edward P. Herbst.

Author/Creator:
Herbst, Edward P., author.
Publication:
Princeton, NJ : Princeton University Press, [2015]
Format/Description:
Book
1 online resource : 34 line illustrations 23 tables.
Series:
The Econometric and Tinbergen Institutes Lectures
Contained In:
De Gruyter University Press Library.
Status/Location:
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Details

Subjects:
Bayesian statistical decision theory.
Econometrics.
Equilibrium (Economics) -- Mathematical models.
Stochastic analysis.
Language:
In English.
System Details:
Mode of access: Internet via World Wide Web.
text file PDF
Summary:
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 function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations.Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions.
Contents:
Frontmatter
Contents
Figures
Tables
Series Editors' Introduction
Preface
Part I. Introduction to DSGE Modeling and Bayesian Inference
1. DSGE Modeling
2. Turning a DSGE Model into a Bayesian Model
3. A Crash Course in Bayesian Inference
Part II. Estimation of Linearized DSGE Models
4. Metropolis-Hastings Algorithms for DSGE Models
5. Sequential Monte Carlo Methods
6. Three Applications
Part III. Estimation of Nonlinear DSGE Models
7. From Linear to Nonlinear DSGE Models
8. Particle Filters
9. Combining Particle Filters with MH Samplers
10. Combining Particle Filters with SMC Samplers
Appendix A. Model Descriptions
Appendix B. Data Sources
Bibliography
Index
Notes:
Description based on online resource; title from PDF title page (publisher's Web site, viewed 08. Jul 2019)
Contributor:
Schorfheide, Frank, author.
De Gruyter.
ISBN:
9781400873739
OCLC:
930489389
Publisher Number:
10.1515/9781400873739 doi
Access Restriction:
Restricted for use by site license.