Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/168391
Authors: 
Mickelsson, Glenn
Year of Publication: 
2015
Series/Report no.: 
Working Paper, Department of Economics, Uppsala University 2015:6
Abstract: 
DSGE models are typically estimated using Bayesian methods, but a researcher may want to estimate a DSGE model with full information maximum likelihood (FIML) so as to avoid the use of prior distributions. A very robust algorithm is needed to find the global maximum within the relevant parameter space. I suggest such an algorithm and show that it is possible to estimate the model of Smets and Wouters (2007) using FIML. Inference is carried out using stochastic bootstrapping techniques. Several FIML estimates turn out to be significantly different from the Bayesian estimates and the reasons behind those differences are analyzed.
Subjects: 
Bayesian methods
Maximum likelihood
Business Cycles
Estimate DSGE models
JEL: 
C11
E32
E37
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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