An alternative approach for the numerical solution of seemingly unrelated regression equations models

Abstract

An alternative approach to compute the coefficients of a Seemingly Unrelated Regression Equations (SURE) model is proposed. Orthogonal transformations are employed to avoid the difficulties in directly computing the inverse of the variance-covariance matrix (or its estimate) which often lead to unnecessary loss of accuracy. The solution of the special SURE model where the problem is constrained so that the regressors in each equation contain the regressors in previous equations as a proper subset, is considered in detail.