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

Helmut Lütkepohl and Aleksei Netšunajev

No 5308, CESifo Working Paper Series from CESifo

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)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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