Bayesian Estimation of DSGE Models /

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

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 i...

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Bibliographic Details
Superior document:Title is part of eBook package: De Gruyter Princeton University Press Complete eBook-Package 2016
VerfasserIn:
Herbst, Edward P.,
Schorfheide, Frank,
Place / Publishing House:Princeton, NJ : : Princeton University Press, , [2015]
©2016
Year of Publication:2015
Language:English
Series:The Econometric and Tinbergen Institutes Lectures
Online Access:
Physical Description:1 online resource (296 p.) :; 34 line illus. 23 tables.
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Table of 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

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