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Tests of Rank in Reduced Rank Regression Models

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Author Info
Gonzalo Camba-Mendez
George Kapetanios
Richard J. Smith
Martin Weale ()

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Abstract

Recently, there has been renewed research interest in the development of tests of the rank of a matrix based on a root-T consistent estimator. This paper evaluates the performance of some asymptotic tests of rank determination in reduced rank regression models through simulation experiments together with their bootstrapped versions. The bootstrapped procedures significantly improve upon the performance of the cor- responding asymptotic tests. The tests of rank considered are applied to construct reduced rank VAR models of leading indicators of UK economic activity and these more parsimonious multivariate representations improve the forecasting performance of VAR models.

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Paper provided by National Institute of Economic and Social Research in its series NIESR Discussion Papers with number 150.

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Date of creation: Jun 1999
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Handle: RePEc:nsr:niesrd:150

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  1. Cubadda, Gianluca, 2004. "A Reduced Rank Regression Approach to Coincident and Leading Indexes Building," Economics & Statistics Discussion Papers esdp04022, University of Molise, Dept. SEGeS. [Downloadable!]
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  2. Kapetanios, George & Marcellino, Massimiliano, 2006. "Impulse Response Functions from Structural Dynamic Factor Models: A Monte Carlo Evaluation," CEPR Discussion Papers 5621, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  3. Stephen G. Donald & Natércia Fortuna & Vladas Pipiras, 2005. "On rank estimation in symmetric matrices: the case of indefinite matrix estimators," FEP Working Papers 167, Universidade do Porto, Faculdade de Economia do Porto. [Downloadable!]
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  4. Fujiwara, Ippei & Koga, Maiko, 2004. "A Statistical Forecasting Method for Inflation Forecasting: Hitting Every Vector Autoregression and Forecasting under Model Uncertainty," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 22(1), pages 123-42, March. [Downloadable!]
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