A note on identification patterns in DSGE models - Michal Andrle (European Central Bank (ECB), 2010)
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.
Keywords: F31; F41; 330; DSGE; Identification; information matrix; rank; singular value decomposition; Dynamisches Gleichgewicht; Dekompositionsverfahren; Algorithmus; Korrelation; Theorie