A Topological View on the Identification of Vector Autoregressions

Neusser, Klaus (2016). A Topological View on the Identification of Vector Autoregressions. Economics letters, 144, pp. 107-111. Elsevier 10.1016/j.econlet.2016.05.003

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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 which becomes relevant, among other things, for the specification of vector autoregressions with time-varying covariance matrices.

Item Type:

Journal Article (Original Article)

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

ISSN:

0165-1765

Publisher:

Elsevier

Language:

English

Submitter:

Eva Marina Zuberbühler

Date Deposited:

04 Jul 2017 11:14

Last Modified:

21 Sep 2017 01:57

Publisher DOI:

10.1016/j.econlet.2016.05.003

BORIS DOI:

10.7892/boris.93188

URI:

https://boris.unibe.ch/id/eprint/93188

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