Semiparametric Cointegrating Rank Selection

24 Pages Posted: 21 May 2008

See all articles by Xu Cheng

Xu Cheng

University of Pennsylvania - Department of Economics

Peter C. B. Phillips

University of Auckland Business School; Yale University - Cowles Foundation; Singapore Management University - School of Economics

Date Written: May 1, 2008


Some convenient limit properties of usual information criteria are given for cointegrating rank selection. Allowing for a nonparametric 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 -> infinity. 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 speci…cation of a full model, is convenient for practical implementation in empirical work, and is sympathetic with semiparametric estimation approaches to cointegration analysis. Some simulations results on …nite sample performance of the criterion are reported.

Keywords: Cointegrating rank, Consistency, Information criteria, Model selection, Nonparametric, Short memory, Unit roots

JEL Classification: C22, C32

Suggested Citation

Cheng, Xu and Phillips, Peter C. B., Semiparametric Cointegrating Rank Selection (May 1, 2008). Cowles Foundation Discussion Paper No. 1658, Available at SSRN:

Xu Cheng

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
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Peter C. B. Phillips (Contact Author)

University of Auckland Business School ( email )

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Yale University - Cowles Foundation ( email )

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