Full Citation

Title: Simple Tests for Reduced Rank in Multivariate Regression

Citation Type: Working Paper

Publication Year: 2002

ISBN:

ISSN:

DOI:

NSFID:

PMCID:

PMID:

Abstract: The present work proposes tests for reduced rank in multivariate regression coefficient matrices, under rather general conditions. A heuristic approach is to first estimate the regressions via standard methods, then compare the coefficient matrix rows (or columns) to assess their redundancy. A formal version of this approach utilizes the distance between an unrestricted coefficient matrix estimate and an estimate restricted by reduced rank. Two distance minimization problems emerge, based on equivalent formulations of the null hypothesis. For each method we derive estimators and tests, and their asymptotic distributions. We examine test performance in simulation, and give some numerical examples.

User Submitted?: No

Authors: Gilbert, Scott; Zemcik, Petr

Series Title:

Publication Number:

Institution: Southern Illinois University Carbondale

Pages:

Publisher Location: Illinois

Data Collections: IPUMS USA

Topics: Methodology and Data Collection, Other

Countries: