A new unique impulse response function in linear vector autoregressive models

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Abstract

This article proposes a new unique impulse response function (IRF) measure, or MIRF, based on the popular vector autoregressive model to study interdependency of multivariate time series. Same as the orthogonal IRF, the estimator of MIRF has an analytical form with well-established asymptotics, and is invariant to ordering of series. Compared to alternative unique IRF measures, MIRF does not depend on extreme identifications, and the associated forecast error variance measure is explainable. An illustrative empirical example is also provided.
Original languageEnglish
Pages (from-to)460-468
Number of pages9
JournalInternational Review of Finance
Volume23
Issue number2
Early online date3 Oct 2022
DOIs
Publication statusPublished - Jun 2023

Bibliographical note

© 2022 The Author. International Review of Finance published by John Wiley & Sons Australia, Ltd on behalf of International Review of Finance Ltd. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • eigendecomposition
  • forecast error variance decomposition
  • impulse response function
  • vector autoregressive

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