EFFICIENT ESTIMATION WITH GROUPED DATA

We investigate efficient estimation when sample is drawn from several heterogenous groups. GLS adjusting inter-group heteroskedasticity is o ften used in this circumstance. But, the error variances conditional o n the regressors could be different within each group. Focusing on thi s two tier heteroskedasticity problem, we propose an estimator that is asymptotically identical to GLS when no conditional heteroskedasticit y is present, and otherwise more efficient. (C) 1998 Elsevier Science S.A.