Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/77747 
Year of Publication: 
2010
Citation: 
[Journal:] SERIEs - Journal of the Spanish Economic Association [ISSN:] 1869-4195 [Volume:] 1 [Issue:] 1/2 [Publisher:] Springer [Place:] Heidelberg [Year:] 2010 [Pages:] 3-49
Publisher: 
Springer, Heidelberg
Abstract: 
In this paper, I review the literature on the formulation and estimation of dynamic stochastic general equilibrium (DSGE) models with a special emphasis on Bayesian methods. First, I discuss the evolution of DSGE models over the last couple of decades. Second, I explain why the profession has decided to estimate these models using Bayesian methods. Third, I briefly introduce some of the techniques required to compute and estimate these models. Fourth, I illustrate the techniques under consideration by estimating a benchmark DSGE model with real and nominal rigidities. I conclude by offering some pointers for future research.
Subjects: 
DSGE models
likelihood estimation
Bayesian methods
JEL: 
C11
C13
E30
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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