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Structural Vector Autoregressions with Heteroskedasticy

Helmut Lütkepohl () and Aleksei Netšunajev ()

No SFB649DP2015-015, SFB 649 Discussion Papers from Humboldt University, Collaborative Research Center 649

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; identi cation via heteroskedasticity; conditional heteroskedasticity; smooth transition; Markov switching; GARCH (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
Date: 2015-03
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