A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjusted) values.
Seemingly Unrelated Regression Model to Measure the Profitability of Some Iraqi Private Commercial Banks with Presence of Outliers
Seemingly uncorrelated regression (SUR)
Outliers
Contemporaneous Correlation
GLS Estimation Method
Robust SUR Estimators
FastSUR Estimator.