Generalized Canonical Regression

33 Pages Posted: 26 Jul 2007

Date Written: June 2007

Abstract

This paper introduces a generalized approach to canonical regression, in which a set of jointly dependent variables enters the left-hand side of the equation as a linear combination, formally like the linear combination of regressors in the right-hand side of the equation. Natural applications occur when the dependent variable is the sum of components that may optimally receive unequal weights or in time series models in which the appropriate timing of the dependent variable is not known a priori. The paper derives a quasi-maximum likelihood estimator as well as its asymptotic distribution and provides illustrative applications.

Keywords: linear regression, time series, canonical correlations

JEL Classification: C51, C22

Suggested Citation

Estrella, Arturo, Generalized Canonical Regression (June 2007). FRB of New York Staff Report No. 288, Available at SSRN: https://ssrn.com/abstract=1003174 or http://dx.doi.org/10.2139/ssrn.1003174
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