Statistical Tests and Estimators of the Rank of a Matrix and Their Applications in Econometric Modelling
Testing and estimating the rank of a matrix of estimated parameters is key in a large variety of econometric modelling scenarios. This article describes general methods to test for and estimate the rank of a matrix, and provides details on a variety of modelling scenarios in the econometrics literature where such methods are required. Four different methods to test for the true rank of a general matrix are described, as well as one method that can handle the case of a matrix subject to parameter constraints associated with defineteness structures. The technical requirements for the implementation of the tests of rank of a general matrix differ and hence there are merits to all of them that justify their use in applied work. Nonetheless, we review available evidence of their small sample properties in the context of different modelling scenarios where all, or some, are applicable.
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Volume (Year): 28 (2009)
Issue (Month): 6 ()
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gonzalo Camba-Mendez & George Kapetanios, 2005.
"Estimating the Rank of the Spectral Density Matrix,"
Journal of Time Series Analysis,
Wiley Blackwell, vol. 26(1), pages 37-48, 01.
- Camba-Méndez, Gonzalo & Kapetanios, George, 2004. "Estimating the rank of the spectral density matrix," Working Paper Series 0349, European Central Bank.