Structural Vector Autoregressions with Heteroskedasticity: A Comparison of Different Volatility Models

35 Pages Posted: 8 Apr 2015

See all articles by Helmut Luetkepohl

Helmut Luetkepohl

German Institute for Economic Research (DIW Berlin)

Aleksei Netsunajev

Free University of Berlin (FUB)

Multiple version iconThere are 2 versions of this paper

Date Written: March 2015

Abstract

A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive (VAR) analysis. A number of different models for heteroskedasticity or conditional heteroskedasticity are proposed and used in applications in this context. This study reviews the different volatility models and points out their advantages and drawbacks. It thereby enables researchers wishing to use identification of structural VAR models via heteroskedasticity to make a more informed choice of a suitable model for a specific empirical analysis. An application investigating the interaction between U.S. monetary policy and the stock market is used to illustrate the related issues.

Keywords: Structural vector autoregression, identification via heteroskedasticity, conditional heteroskedasticity, smooth transition, Markov switching, GARCH

JEL Classification: C32

Suggested Citation

Luetkepohl, Helmut and Netsunajev, Aleksei, Structural Vector Autoregressions with Heteroskedasticity: A Comparison of Different Volatility Models (March 2015). DIW Berlin Discussion Paper No. 1464, Available at SSRN: https://ssrn.com/abstract=2591392 or http://dx.doi.org/10.2139/ssrn.2591392

Helmut Luetkepohl (Contact Author)

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstraße 58
Berlin, 10117
Germany

Aleksei Netsunajev

Free University of Berlin (FUB) ( email )

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

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