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Tests of rank in reduced rank regression models

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UNSPECIFIED (2003) Tests of rank in reduced rank regression models. JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 21 (1). pp. 145-155. doi:10.1198/073500102288618847

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Official URL: http://dx.doi.org/10.1198/073500102288618847

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Abstract

There has recently been renewed research interest in the development of tests of the rank of a matrix. This article evaluates the performance of some asymptotic tests of rank determination in reduced rank regression models together with bootstrapped versions through simulation experiments. The bootstrapped procedures significantly improve on the performance of the corresponding asymptotic tests. The article also presents a Monte Carlo exercise comparing the forecasting performance of reduced rank and unrestricted vector autoregressive (VAR) models in which the former appear superior. The tests of rank considered here are then applied to construct reduced rank VAR models for leading indicators of U.K. economic activity. These more parsimonious multivariate representations display an improvement in forecasting performance over that of unrestricted VAR models.

Item Type: Journal Article
Subjects: H Social Sciences > HC Economic History and Conditions
H Social Sciences
Q Science > QA Mathematics
Journal or Publication Title: JOURNAL OF BUSINESS & ECONOMIC STATISTICS
Publisher: AMER STATISTICAL ASSOC
ISSN: 0735-0015
Official Date: January 2003
Dates:
DateEvent
January 2003UNSPECIFIED
Volume: 21
Number: 1
Number of Pages: 11
Page Range: pp. 145-155
DOI: 10.1198/073500102288618847
Publication Status: Published

Data sourced from Thomson Reuters' Web of Knowledge

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