Identifying cointegration by eigenanalysis

Rongmao Zhang, Peter Robinson and Qiwei Yao

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We propose a new and easy-to-use method for identifying cointegrated components of nonstationary time series, consisting of an eigenanalysis for a certain non-negative definite matrix. Our setting is model-free, and we allow the integer-valued integration orders of the observable series to be unknown, and to possibly differ. Consistency of estimates of the cointegration space and cointegration rank is established both when the dimension of the observable time series is fixed as sample size increases, and when it diverges slowly. The proposed methodology is also extended and justified in a fractional setting. A Monte Carlo study of finite-sample performance, and a small empirical illustration, are reported. Supplementary materials for this article are available online.

Keywords: cointegration; eigenanalysis; i(d); nonstationary processes; cector time series (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2019-04-03
New Economics Papers: this item is included in nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

Published in Journal of the American Statistical Association, 3, April, 2019, 114(526), pp. 916 - 927. ISSN: 0162-1459

Downloads: (external link)
http://eprints.lse.ac.uk/87431/ Open access version. (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: https://EconPapers.repec.org/RePEc:ehl:lserod:87431

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().