A Topological View on the Identification of Structural Vector Autoregressions

Neusser, Klaus (March 2016). A Topological View on the Identification of Structural Vector Autoregressions (Discussion Papers 16-04). Bern: Department of Economics

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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.

Item Type:

Working Paper

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Economics

UniBE Contributor:

Neusser, Klaus

Subjects:

300 Social sciences, sociology & anthropology > 330 Economics

Series:

Discussion Papers

Publisher:

Department of Economics

Language:

English

Submitter:

Lars Tschannen

Date Deposited:

28 Dec 2020 08:55

Last Modified:

28 Dec 2020 08:55

JEL Classification:

C1, C18, C32

BORIS DOI:

10.48350/145828

URI:

https://boris.unibe.ch/id/eprint/145828

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