A solution to the global identification problem in DSGE models

Andrzej Kocięcki and Marcin Kolasa

No 2022-01, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: We develop an analytical framework to study global identification in structural models with forward-looking expectations. Our identification condition combines the similarity transformation linking the observationally equivalent state space systems with the constraints imposed on them by the model parameters. The key step of solving the identification problem then reduces to finding all roots of a system of polynomial equations. We show how it can be done using the concept of a Gröbner basis and recently developed algorithms to compute it analytically. In contrast to papers relying on numerical search, our approach can effectively prove whether a model is identified or not at the given parameter point, explicitly delivering the complete set of observationally equivalent parameter vectors. We present the solution to the global identification problem for several popular DSGE models. Our findings indicate that observational equivalence in medium-sized models of this class might be actually not as widespread as suggested by earlier, small model-based evidence.

Keywords: global identification; state space systems; DSGE models; Gröbner basis (search for similar items in EconPapers)
JEL-codes: C10 C51 C65 E32 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2022
New Economics Papers: this item is included in nep-dge, nep-ecm and nep-ets
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https://www.wne.uw.edu.pl/download_file/1246/0 First version, 2022 (application/pdf)

Related works:
Journal Article: A solution to the global identification problem in DSGE models (2023)
Working Paper: A solution to the global identification problem in DSGE models (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:war:wpaper:2022-01

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