Do Bivariate SVAR Models with Long-Run Identifying Restrictions Yield Reliable Results? An Investigation into the Case of Germany

Jan Gottschalk and Willem Van Zandweghe ()

Swiss Journal of Economics and Statistics (SJES), 2003, vol. 139, issue I, pages 55-81

Abstract: Bivariate SVAR models employing long-run identifying restrictions are popular tools to investigate the source of business cycle fluctuations. Their advantage is the simplicity in use and interpretation. However, their low dimension may also lead to a failure of the identification procedure, with the result that the identified shocks are a mixture of the 'true' shocks. To investigate this issue, the consistency of results from different bivariate SVAR models estimated for German data is evaluated using the FAUST and LEEPER (1997) test procedure. The principal result is that these models do not allow reliable inference on the sources of output fluctuations.

Keywords: Business Cycle Fluctuations; Structural Vector Autoregression Models; Long-run Restrictions (search for similar items in EconPapers)
JEL-codes: E32 C32 (search for similar items in EconPapers)
Date: 2003
View list of references

Downloads: (external link)
http://www.sjes.ch/papers/2003-I-3.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:ses:arsjes:2003-i-3

Access Statistics for this article

Swiss Journal of Economics and Statistics (SJES) is edited by Klaus Neusser

More articles in Swiss Journal of Economics and Statistics (SJES) from Swiss Society of Economics and Statistics (SSES)
Contact information at EDIRC.
Series data maintained by Peter Steiner ().