Structural vector autoregressions with heteroskedasticity: A comparison of different volatility models

Helmut Lütkepohl and Aleksei Netšunajev

No 2015-015, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive (VAR) analysis. A number of di erent models for heteroskedasticity or conditional heteroskedasticity are proposed and used in applications in this context. This study reviews the di erent volatility models and points out their advantages and drawbacks. It thereby enables researchers wishing to use identi cation of structural VAR models via heteroskedasticity to make a more informed choice of a suitable model for a speci c 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)
Date: 2015
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https://www.econstor.eu/bitstream/10419/119426/1/821918567.pdf (application/pdf)

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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