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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2015-015

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
• Subject: structural vector autoregression ; identification via heteroskedasticity ; conditional heteroskedasticity ; smooth transition ; Markov switching ; GARCH

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lütkepohl, Helmut ; Netšunajev, Aleksei
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2015

Further information

• Handle: http://hdl.handle.net/10419/119426
• Last update: 10.03.2025, 11:44 AM CET