Structural Vector Autoregressions : Checking Identifying Long-Run Restrictions via Heteroskedasticity

Artikel

Abstract Long-run restrictions have been used extensively for identifying structural shocks in vector autoregressive (VAR) analysis. Such restrictions are typically just-identifying but can be checked by utilizing changes in volatility. This paper reviews and contrasts the volatility models that have been used for this purpose. Three main approaches have been used, exogenously generated changes in the unconditional residual covariance matrix, changing volatility modelled by a Markov switching mechanism and multivariate generalized autoregressive conditional heteroskedasticity models. Using changes in volatility for checking long-run identifying restrictions in structural VAR analysis is illustrated by reconsidering models for identifying fundamental components of stock prices.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Journal of Economic Surveys ; ISSN: 0950-0804 ; Volume: 30 ; Year: 2016 ; Pages: 377-392 ; Hoboken: Wiley

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: vector autoregression ; heteroskedasticity ; vector GARCH ; conditional heteroskedasticity ; Markov switching model

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lütkepohl, Helmut ; Velinov, Anton
• Event: Veröffentlichung
• (who): Wiley ; ZBW – Leibniz Information Centre for Economics
• (where): Hoboken
• (when): 2016

Further information

• DOI: http://onlinelibrary.wiley.com/doi/10.1111/joes.12100/abstract
• Handle: http://hdl.handle.net/10419/180833
• Last update: 10.03.2025, 11:43 AM CET