Reduced-Rank Regression: A Useful Determinant Identity
AbstractWe derive an identity for the determinant of a product involving non-squared matrices. The identity can be used to derive the maximum likelihood estimator in reduced-rank regres- sions with Gaussian innovations. Furthermore, the identity sheds light on the structure of the estimation problem that arises when the reduced-rank parameters are subject to additional constraints.
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Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2008-02.
Date of creation: 15 Jan 2008
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Determinant Identity; Reduced Rank Regression; Least Squares;
Find related papers by JEL classification:
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-06-27 (All new papers)
- NEP-ECM-2008-06-27 (Econometrics)
- NEP-ETS-2008-06-27 (Econometric Time Series)
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