Structural vector autoregressions: Checking identifying long-run restrictions via heteroskedasticity

Helmut Lütkepohl and Anton Velinov

No 2014-009, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

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 (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Date: 2014
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Related works:
Journal Article: STRUCTURAL VECTOR AUTOREGRESSIONS: CHECKING IDENTIFYING LONG-RUN RESTRICTIONS VIA HETEROSKEDASTICITY (2016)
Journal Article: Structural Vector Autoregressions: Checking Identifying Long-Run Restrictions via Heteroskedasticity (2016)
Working Paper: Structural Vector Autoregressions: Checking Identifying Long-run Restrictions via Heteroskedasticity (2014)
Working Paper: Structural Vector Autoregressions: Checking Identifying Long-Run Restrictions via Heteroskedasticity (2014)
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