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

31 Pages Posted: 31 Jan 2014

See all articles by Helmut Luetkepohl

Helmut Luetkepohl

German Institute for Economic Research (DIW Berlin)

Anton Velinov

German Institute for Economic Research (DIW Berlin)

Multiple version iconThere are 2 versions of this paper

Date Written: January 2014

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 (GARCH) 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.

Keywords: Vector autoregression, heteroskedasticity, vector GARCH, conditional heteroskedasticity, Markov switching model

JEL Classification: C32

Suggested Citation

Luetkepohl, Helmut and Velinov, Anton, Structural Vector Autoregressions: Checking Identifying Long-Run Restrictions via Heteroskedasticity (January 2014). DIW Berlin Discussion Paper No. 1356, Available at SSRN: https://ssrn.com/abstract=2388145 or http://dx.doi.org/10.2139/ssrn.2388145

Helmut Luetkepohl (Contact Author)

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstraße 58
Berlin, 10117
Germany

Anton Velinov

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstraße 58
Berlin, 10117
Germany

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