Title

Semiparametric Cointegrating Rank Selection

Publication Type

Journal Article

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: 24 months

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