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A note on identification patterns in DSGE models

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  • Andrle, Michal

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. JEL Classification: F31, F41

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 1235.

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Date of creation: Aug 2010
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Handle: RePEc:ecb:ecbwps:20101235

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Related research

Keywords: DSGE; Identification; information matrix; rank; singular value decomposition;

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References

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  1. Zellner, Arnold, 1985. "Bayesian Econometrics," Econometrica, Econometric Society, vol. 53(2), pages 253-69, March.
  2. Guerron-Quintana, Pablo A. & Inoue, Atsushi & Kilian, Lutz, 2009. "Frequentist Inference in Weakly Identified DSGE Models," CEPR Discussion Papers 7447, C.E.P.R. Discussion Papers.
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Cited by:
  1. Müller, Ulrich K., 2012. "Measuring prior sensitivity and prior informativeness in large Bayesian models," Journal of Monetary Economics, Elsevier, vol. 59(6), pages 581-597.
  2. Evren Caglar & Jagjit S. Chadha & Katsuyuki Shibayama, 2012. "Bayesian Estimation of DSGE Models: Is the Workhorse Model Identified?," Koç University-TUSIAD Economic Research Forum Working Papers 1205, Koc University-TUSIAD Economic Research Forum.

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