Chapter 9. Solution and Estimation Methods for DSGE Models

This chapter provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field.

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Year of publication:	2016
Authors:	Fernández-Villaverde, J. ; Rubio-Ramírez, J.F. ; Schorfheide, F.
Published in:	Handbook of macroeconomics : volume 2, v. 2A-2B SET. - Saint Louis : Elsevier Science, ISBN 978-0-444-59488-4. - 2016, p. 527-724
Subject:	Approximation error analysis \| Bayesian inference \| DSGE model \| Frequentist inference \| GMM estimation \| Impulse response function matching \| Likelihood-based inference \| Metropolis-Hastings algorithm \| Minimum distance estimation \| Particle filter \| Perturbation methods \| Projection methods \| Sequential Monte Carlo. \| Schätztheorie \| Estimation theory \| Dynamisches Gleichgewicht \| Dynamic equilibrium \| Monte-Carlo-Simulation \| Monte Carlo simulation \| Induktive Statistik \| Statistical inference \| Bayes-Statistik \| DSGE-Modell \| Momentenmethode \| Method of moments \| Algorithmus \| Algorithm

Type of publication:	Article
Language:	English
Other identifiers:	10.1016/bs.hesmac.2016.03.006 [DOI]
Classification:	C11 - Bayesian Analysis ; C13 - Estimation ; C32 - Time-Series Models ; C52 - Model Evaluation and Testing ; C61 - Optimization Techniques; Programming Models; Dynamic Analysis ; C63 - Computational Techniques ; E32 - Business Fluctuations; Cycles ; E52 - Monetary Policy (Targets, Instruments, and Effects)
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014024288