A Topological View on the Identification of Structural Vector Autoregressions

Klaus Neusser ()

Diskussionsschriften from Universitaet Bern, Departement Volkswirtschaft

Abstract: The notion of the group of orthogonal matrices acting on the set of all feasible identification schemes is used to characterize the identification problem arising in structural vector autoregressions. This approach presents several conceptual advantages. First, it provides a fundamental justification for the use of the normalized Haar measure as the natural uninformative prior. Second, it allows to derive the joint distribution of blocks of parameters defining an identification scheme. Finally, it provides a coherent way for studying perturbations of identification schemes becomes relevant, among other things, for the specification of vector autoregressions with time-varying covariance matrices

Keywords: SVAR; identification; group action; Haar measure; perturbation (search for similar items in EconPapers)
JEL-codes: C1 C18 C32 (search for similar items in EconPapers)
Date: 2016-03
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (2)

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Journal Article: A topological view on the identification of structural vector autoregressions (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:ube:dpvwib:dp1604

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