Reduced Rank Regression

Søren Johansen

doi:10.1057/9780230226203.1410

Reduced Rank Regression

Økonomisk Institut

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

Originalsprog	Engelsk
Titel	The New Palgrave Dictionary of Economics
Redaktører	Steven N. Durlauf, Lawrence E. Blume
Antal sider	7
Forlag	Palgrave Macmillan
Publikationsdato	2008
Udgave	2
ISBN (Trykt)	9780333786765
DOI	https://doi.org/10.1057/9780230226203.1410
Status	Udgivet - 2008

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10.1057/9780230226203.1410

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AB - 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

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Reduced Rank Regression

Abstract

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