Non-identifiability of VMA and VARMA systems in the mixed frequency case
Manfred Deistler,
Lukas Koelbl and
Brian D.O. Anderson
Econometrics and Statistics, 2017, vol. 4, issue C, 31-38
Abstract:
Recently, identifiability results for VAR systems in the context of mixed frequency data have been shown in a number of papers. These results have been extended to VARMA systems, where the MA order is smaller than or equal to the AR order. Here, it is shown that in the VMA case and in the VARMA case, where the MA order exceeds the AR order, results are completely different. Then, for the case, where the innovation covariance matrix is non-singular, “typically” non-identifiability occurs – not even local identifiability. This is due to the fact that, e.g., in the VMA case, as opposed to the VAR case, the not directly observed autocovariances of the output can vary “freely”. In the singular case, i.e., when the innovation covariance matrix is singular, things may be different.
Keywords: VARMA; VMA; Mixed frequency; Non-identifiability (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S2452306216300302
Full text for ScienceDirect subscribers only. Contains open access articles
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: https://EconPapers.repec.org/RePEc:eee:ecosta:v:4:y:2017:i:c:p:31-38
DOI: 10.1016/j.ecosta.2016.11.006
Access Statistics for this article
Econometrics and Statistics is currently edited by E.J. Kontoghiorghes, H. Van Dijk and A.M. Colubi
More articles in Econometrics and Statistics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().