Fully modified estimation with cross-equation restrictions

A transformation is introduced which allows Fully Modified estimation of a Seemingly Unrelated Regression model with cross-equation restrictions. Two alternative methods of correcting for endogeneity are suggested. One uses the long run covariance matrices associated with untransformed innovations in the regressors and the other uses those associated with the transformed innovations. The former approach is shown to be asymptotically efficient