Testing Identification via Heteroskedasticity in Structural Vector Autoregressive Models

28 Pages Posted: 21 Oct 2018

See all articles by Helmut Lütkepohl

Helmut Lütkepohl

Free University of Berlin (FUB)

Mika Meitz

University of Helsinki - Department of Political and Economic Studies

Aleksei Netsunajev

Free University of Berlin (FUB)

Pentti Saikkonen

University of Helsinki - Department of Statistics

Date Written: October 1, 2018

Abstract

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.

Keywords: Heteroskedasticity, structural identification, vector autoregressive process

JEL Classification: C32

Suggested Citation

Lütkepohl, Helmut and Meitz, Mika and Netsunajev, Aleksei and Saikkonen, Pentti, Testing Identification via Heteroskedasticity in Structural Vector Autoregressive Models (October 1, 2018). DIW Berlin Discussion Paper No. 1764, Available at SSRN: https://ssrn.com/abstract=3269192 or http://dx.doi.org/10.2139/ssrn.3269192

Helmut Lütkepohl (Contact Author)

Free University of Berlin (FUB)

Otto Suhr Institut for Political Science\
Ihnestrasse 21
Berlin
Germany

Mika Meitz

University of Helsinki - Department of Political and Economic Studies

P.O. Box 54
FIN-00014 Helsinki
Finland

Aleksei Netsunajev

Free University of Berlin (FUB) ( email )

Van't-Hoff-Str. 8
Berlin, Berlin 14195
Germany

Pentti Saikkonen

University of Helsinki - Department of Statistics ( email )

Finland
+09 191 24867 (Phone)

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