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A new biased-estimator for a class of ill-conditioned seemingly unrelated regression systems

Yaoqiong Zhou, Ning Dong, Bo Yu


In this paper, we propose a new biased-estimator for a class of ill-conditioned seemingly unrelated regression systems. Under the criterion of mean dispersion error, we show the new-presented estimator is more efficient than the existing biased-estimators. When the covariance matrix in seemingly unrelated regression systems is unknown, we also derive a two step estimator and discuss its good features.


seemingly unrelated regression system, biased-estimators, mean dispersion error, two step estimator.

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