Department of Economics and Business Economics

Identification and estimation of non-Gaussian structural vector autoregressions

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Markku Lanne
  • Mika Meitz, Helsingin yliopisto
  • ,
  • Pentti Saikkonen, Helsingin yliopisto

Conventional structural vector autoregressive (SVAR) models with Gaussian errors are not identified, and additional identifying restrictions are needed in applied work. We show that the Gaussian case is an exception in that a SVAR model whose error vector consists of independent non-Gaussian components is, without any additional restrictions, identified and leads to essentially unique impulse responses. Building upon this result, we introduce an identification scheme under which the maximum likelihood estimator of the parameters of the non-Gaussian SVAR model is consistent and asymptotically normally distributed. As a consequence, additional economic identifying restrictions can be tested. In an empirical application, we find a negative impact of a contractionary monetary policy shock on financial markets, and clearly reject the commonly employed recursive identifying restrictions.

Original languageEnglish
JournalJournal of Econometrics
Volume196
Issue2
Pages (from-to)288-304
Number of pages17
ISSN0304-4076
DOIs
Publication statusPublished - 1 Feb 2017

    Research areas

  • Identification, Impulse responses, Non-Gaussianity, Structural vector autoregressive model

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