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

Helmut Lütkepohl and Aleksei Netšunajev

No 1464, Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research

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 (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Pages: 32 p.
Date: 2015
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Structural Vector Autoregressions with Heteroskedasticity - A Comparison of Different Volatility Models (2015)
Working Paper: Structural vector autoregressions with heteroskedasticity: A comparison of different volatility models (2015)
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