Reduced-rank regression: A useful determinant identity

We formulate an identity for the determinant of a product involving rectangular matrices. The identity can be used to derive the maximum likelihood estimator in reduced-rank regressions 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.