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 i...
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Full Text (via EBSCO) |
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| Main Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
Princeton :
Princeton University Press,
[2016]
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| Series: | Econometric and Tinbergen Institutes lectures.
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| Subjects: |
MARC
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| 100 | 1 | |a Herbst, Edward P., |d 1984- |e author. |0 http://id.loc.gov/authorities/names/n2015039165 |1 http://isni.org/isni/0000000419056258. | |
| 245 | 1 | 0 | |a Bayesian estimation of DSGE models / |c Edward P. Herbst and Frank Schorfheide. |
| 264 | 1 | |a Princeton : |b Princeton University Press, |c [2016] | |
| 264 | 4 | |c ©2016. | |
| 300 | |a 1 online resource (xix, 275 pages) | ||
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| 490 | 1 | |a The Econometric and Tinbergen Institutes lectures. | |
| 504 | |a Includes bibliographical references (pages 257-269) and index. | ||
| 505 | 0 | |a Introduction to DSGE modeling and Bayesian inference -- DSGE modeling -- Turning a DSGE model into a Bayesian Model -- A crash course in Bayesian inference -- Estimation of linearized DSGE models -- Metropolis-Hasting algorithms for DSGE models -- Sequential Monte Carlo methods -- Three applications -- Estimation of nonlinear DSGE models -- From linear to nonlinear DSGE models -- Particle filters -- Combining particle filters with MH samplers -- Combining particle filters with SMC samplers. | |
| 520 | |a 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.-- |c Provided by publisher. | ||
| 546 | |a In English. | ||
| 588 | 0 | |a Print version record. | |
| 650 | 0 | |a Equilibrium (Economics) |x Mathematical models. |0 http://id.loc.gov/authorities/subjects/sh2008102574. | |
| 650 | 0 | |a Bayesian statistical decision theory. |0 http://id.loc.gov/authorities/subjects/sh85012506. | |
| 650 | 0 | |a Stochastic analysis. |0 http://id.loc.gov/authorities/subjects/sh85128175. | |
| 650 | 0 | |a Econometrics. |0 http://id.loc.gov/authorities/subjects/sh85040763. | |
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| 650 | 7 | |a Stochastic analysis. |2 fast |0 (OCoLC)fst01133499. | |
| 700 | 1 | |a Schorfheide, Frank, |e author. |0 http://id.loc.gov/authorities/names/nr2002041522 |1 http://isni.org/isni/0000000050198255. | |
| 776 | 0 | 8 | |i Print version: |a Herbst, Edward P., 1984- |t Bayesian estimation of DSGE models. |d Princeton : Princeton University Press, [2016] |z 9780691161082 |w (DLC) 2015023799 |w (OCoLC)934585068. |
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