Testing identification via heteroskedasticity in structural vector autoregressive models

Helmut Lütkepohl, Mika Harri Meitz, Aleksei Netšunajev, Pentti Juhani Saikkonen

Research output: Contribution to journalArticleScientific


Tests for identification through heteroskedasticity in structural vector autoregressive analysis are developed for models with two volatility states where the time point of volatility change is known. The tests are Wald type tests for which only the unrestricted model including the covariance matrices of the two volatility states have to be estimated. The residuals of the model are assumed to be from the class of elliptical distributions which includes Gaussian models. The asymptotic null distributions of the test statistics are derived and simulations are used to explore their small sample properties. Two empirical examples illustrate the usefulness of the tests.
Original languageEnglish
JournalDIW Discussion Papers
Issue number1764
Number of pages26
Publication statusPublished - Oct 2018
MoE publication typeB1 Journal article

Fields of Science

  • 511 Economics

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