Journal of the American Statistical Association · 1974 · 41 citations · 10 references
Natural SciencesBiostatisticsEconometricsStatistical ModelingStatisticsEstimation TheoryInferential StatisticsRandom-effects ModelsRegressionStatistical InferenceAsymptotic Distribution TheoryCovariance Matrix EstimationEstimation Of Regression ModelsGeneralized Least Squares EstimationRandom Coefficients ModelsRegression EstimationSeemingly Unrelated RegressionStatistical Regression Estimation
Abstract This article deals with the problem of estimating the set of seemingly unrelated regressions (SUR) when the regression coefficients are random. In the article, an estimator has been proposed which is consistent and has the same asymptotic normal distribution as the Aitken generalized least squares estimator which assumes the covariance matrix to be known. Further, it has been shown that the proposed estimator is asymptotically more efficient than Zellner's SUR estimator provided that the true model is one with random coefficients.
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