Tests of rank in reduced rank regression models
UNSPECIFIED. (2003) Tests of rank in reduced rank regression models. JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 21 (1). pp. 145-155. ISSN 0735-0015Full text not available from this repository.
Official URL: http://dx.doi.org/10.1198/073500102288618847
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|
|Number of Pages:||11|
|Page Range:||pp. 145-155|
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