Generalized canonical regression

Arturo Estrella ()

No 288, Staff Reports from Federal Reserve Bank of New York

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: Time-series analysis; Econometric models (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: Written 2007
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