Reduced Rank Regression

Søren Johansen

doi:10.1057/9780230226203.1410

Reduced Rank Regression

Department of Economics

Abstract

The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating eigenvalues and eigenvectors. We give a number of different applications to regression and time series analysis, and show how the reduced rank regression estimator can be derived as a Gaussian maximum likelihood estimator. We briefly mention asymptotic results

Original language	English
Title of host publication	The New Palgrave Dictionary of Economics
Editors	Steven N. Durlauf, Lawrence E. Blume
Number of pages	7
Publisher	Palgrave Macmillan
Publication date	2008
Edition	2
ISBN (Print)	9780333786765
DOIs	https://doi.org/10.1057/9780230226203.1410
Publication status	Published - 2008

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10.1057/9780230226203.1410

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Reduced Rank Regression

Abstract

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