Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/153669
Authors: 
Andrle, Michal
Year of Publication: 
2010
Series/Report no.: 
ECB Working Paper 1235
Abstract: 
This paper comments on selected aspects of identification issues of DSGE models. It suggests the singular value decomposition (SVD) as a useful tool for detecting local weak and non-identification. This decomposition is useful for checking rank conditions of identification, identification strength, and it also offers parameter space ‘identification patterns’. With respect to other methods of identification the singular value decomposition is particularly easy to apply and offers an intuitive interpretation. We suggest a simple algorithm for analyzing identification and an algorithm for finding a set of the most identifiable set of parameters. We also demonstrate that the use of bivariate and multiple correlation coefficients of parameters provides only limited check of identification problems.
Subjects: 
DSGE
Identification
information matrix
rank
singular value decomposition
JEL: 
F31
F41
Document Type: 
Working Paper

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