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Bayesian Estimation of DSGE Models (Hardcover) (Edward P. Herbst & Frank Schorfheide)

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About this item

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.

The Description for this book, Bayesian Estimation of DSGE Models, will be forthcoming.

Number of Pages: 275
Genre: Business + Money Management
Sub-Genre: Econometrics, Economics / General, Economics / Theory
Series Title: The Econometric and Tinbergen Institutes Lectures
Format: Hardcover
Publisher: Princeton Univ Pr
Author: Edward P. Herbst & Frank Schorfheide
Language: English
Street Date: December 29, 2015
TCIN: 21563768
UPC: 9780691161082
Item Number (DPCI): 247-49-7316
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