Bayesian Estimation of DSGE Models
Summary
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Bayesian Estimation of DSGE Models by 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 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.
"Well written and well organized, and the topic analyzed is very interesting and current"--Manuel Salvador, MathSciNet
Edward P. Herbst is an economist in the Division of Research and Statistics at the Federal Reserve Board. Frank Schorfheide is Professor of Economics at the University of Pennsylvania and research associate at the National Bureau of Economic Research. He also is a fellow of the Penn Institute for Economic Research, a visiting scholar at the Federal Reserve Banks of Philadelphia and New York, and a coeditor of Quantitative Economics. For more, see edherbst.net and sites.sas.upenn.edu/schorf.
| SKU | NGR9780691161082 |
| ISBN 13 | 9780691161082 |
| ISBN 10 | 0691161089 |
| Title | Bayesian Estimation of DSGE Models |
| Author | Edward P Herbst |
| Series | The Econometric And Tinbergen Institutes Lectures |
| Condition | New |
| Binding Type | Hardback |
| Publisher | Princeton University Press |
| Year published | 2015-12-29 |
| Number of pages | 296 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time |
