Evaluating the strength of identification in DSGE models. An a priori approach

Nikolay Iskrev

Working Papers from Banco de Portugal, Economics and Research Department

Abstract: This paper presents a new approach to parameter identification analysis in DSGE models wherein the strength of identification is treated as property of the underlying model and studied prior to estimation. The strength of identification reflects the empirical importance of the economic features represented by the parameters. Identification problems arise when some parameters are either nearly irrelevant or nearly redundant with respect to the aspects of reality the model is designed to explain. The strength of identification therefore is not only crucial for the estimation of models, but also has important implications for model development. The proposed measure of identification strength is based on the Fisher information matrix of DSGE models and depends on three factors: the parameter values, the set of observed variables and the sample size. By applying the proposed methodology, researchers can determine the effect of each factor on the strength of identification of individual parameters, and study how it is related to structural and statistical characteristics of the economic model. The methodology is illustrated using the medium-scale DSGE model estimated in Smets and Wouters (2007).

JEL-codes: C32 C51 C52 E32 (search for similar items in EconPapers)
Date: 2010
New Economics Papers: this item is included in nep-dge and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33)

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Working Paper: Evaluating the strength of identification in DSGE models. An a priori approach (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:ptu:wpaper:w201032

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