Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/180833 
Erscheinungsjahr: 
2016
Quellenangabe: 
[Journal:] Journal of Economic Surveys [ISSN:] 0950-0804 [Volume:] 30 [Publisher:] Wiley [Place:] Hoboken [Year:] 2016 [Pages:] 377-392
Verlag: 
Wiley, Hoboken
Zusammenfassung: 
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.
Schlagwörter: 
vector autoregression
heteroskedasticity
vector GARCH
conditional heteroskedasticity
Markov switching model
JEL: 
C32
DOI der veröffentlichten Version: 
Dokumentart: 
Article
Dokumentversion: 
Accepted Manuscript (Postprint)

Datei(en):
Datei
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