Bootstrap Statistical Tests of Rank Determination for System Identification

U of London Queen Mary Economics Working Paper No. 468

23 Pages Posted: 26 Feb 2003

Date Written: November 2002

Abstract

Identification in the context of multivariate state space modelling involves the specification of the dimension of the state vector. One identification approach requires an estimate of the rank of a Hankel matrix. The most frequently used approaches of rank determination rely on information criteria methods. This paper evaluates the performance of some asymptotic tests of rank determination together with their bootstrapped versions against standard information criteria methods. This study is conducted through simulation experiments. Results show that the bootstrapped procedures significantly improve upon the performance of the corresponding asymptotic tests, and are proved better than standard Information Criterion methods.

Keywords: Rank, Bootstrap, Monte Carlo, System Identification, Hankel Operator

JEL Classification: C12, C15, C32

Suggested Citation

Camba-Mendez, Gonzalo and Kapetanios, George, Bootstrap Statistical Tests of Rank Determination for System Identification (November 2002). U of London Queen Mary Economics Working Paper No. 468, Available at SSRN: https://ssrn.com/abstract=358290 or http://dx.doi.org/10.2139/ssrn.358290

Gonzalo Camba-Mendez (Contact Author)

European Central Bank (ECB) ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany
0049 69 13440 (Phone)
0044 69 1344 6000 (Fax)

George Kapetanios

King's College, London ( email )

30 Aldwych
London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

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