# Estimation of High-Dimensional Seemingly Unrelated Regression Models

@inproceedings{Tan2018EstimationOH, title={Estimation of High-Dimensional Seemingly Unrelated Regression Models}, author={Lidan Tan and Khai X. Chiong and Hyungsik Roger Moon}, year={2018} }

In this paper, we investigate seemingly unrelated regression (SUR) models that allow the number of equations (N) to be large, and to be comparable to the number of the observations in each equation (T). It is well known in the literature that the conventional SUR estimator, for example, the generalized least squares (GLS) estimator of Zellner (1962) does not perform well. As the main contribution of the paper, we propose a new feasible GLS estimator called the feasible graphical lasso (FGLasso… CONTINUE READING

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