Publication Type
Journal Article
Version
publishedVersion
Publication Date
1-2009
Abstract
Some convenient limit properties of usual information criteria are given for cointegrating rank selection. Allowing for a non-parametric short memory component and using a reduced rank regression with only a single lag, standard information criteria are shown to be weakly consistent in the choice of cointegrating rank provided the penalty coefficient C(n) -> infinity and C(n)/n -> 0 as n -> 8. The limit distribution of the AIC criterion, which is inconsistent, is also obtained. The analysis provides a general limit theory for semiparametric reduced rank regression under weakly dependent errors. The method does not require the specification of a full model, is convenient for practical implementation in empirical work, and is sympathetic with semiparametric estimation approaches to co-integration analysis. Some simulation results on the finite sample performance of the criteria are reported.
Keywords
Cointegrating rank, Consistency, Information criteria, Model selection, Nonparametric, Short memory, Unit roots
Discipline
Econometrics
Research Areas
Econometrics
Publication
Econometrics Journal
Volume
12
Issue
1
First Page
S83
Last Page
S104
ISSN
1368-4221
Identifier
10.1111/j.1368-423X.2008.00270.x
Publisher
Wiley
Citation
CHENG, Xu and Peter C. B. PHILLIPS.
Semiparametric Cointegrating Rank Selection. (2009). Econometrics Journal. 12, (1), S83-S104.
Available at: https://ink.library.smu.edu.sg/soe_research/1807
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1111/j.1368-423X.2008.00270.x