On the Identification of Fractionally Cointegrated VAR Models With the Condition
Federico Carlini and
Paolo Santucci de Magistris
Journal of Business & Economic Statistics, 2019, vol. 37, issue 1, 134-146
Abstract:
This article discusses identification problems in the fractionally cointegrated system of Johansen and Johansen and Nielsen. It is shown that several equivalent reparametrizations of the model associated with different fractional integration and cointegration parameters may exist for any choice of the lag-length when the true cointegration rank is known. The properties of these multiple nonidentified models are studied and a necessary and sufficient condition for the identification of the fractional parameters of the system is provided. The condition is named F(d)$\mathcal {F}(d)$. This is a generalization of the well-known I(1) condition to the fractional case. Imposing a proper restriction on the fractional integration parameter, d, is sufficient to guarantee identification of all model parameters and the validity of the F(d)$\mathcal {F}(d)$ condition. The article also illustrates the indeterminacy between the cointegration rank and the lag-length. It is also proved that the model with rank zero and k lags may be an equivalent reparameterization of the model with full rank and k − 1 lags. This precludes the possibility to test for the cointegration rank unless a proper restriction on the fractional integration parameter is imposed.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2017.1294077 (text/html)
Access to full text is restricted to subscribers.
Related works:
Working Paper: On the identification of fractionally cointegrated VAR models with the F(d) condition (2014) 
Working Paper: On the identification of fractionally cointegrated VAR models with the F(d) condition (2013) 
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: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:37:y:2019:i:1:p:134-146
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20
DOI: 10.1080/07350015.2017.1294077
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan
More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().