Risk comparison of the Stein-rule estimator in a linear regression model with omitted relevant regressors and multivariatet errors under the Pitman nearness criterion

被引:0
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作者
Akio Namba
Kazuhiro Ohtani
机构
[1] Kobe University,Gradute School of Economics
来源
Statistical Papers | 2007年 / 48卷
关键词
Mean Square Error; Ordinary Little Square; Linear Regression Model; Specification Error; Ordinary Little Square Estimator;
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摘要
In this paper we consider a linear regression model with omitted relevant regressors and multivariatet error terms. The explicit formula for the Pitman nearness criterion of the Stein-rule (SR) estimator relative to the ordinary least squares (OLS) estimator is derived. It is shown numerically that the dominance of the SR estimator over the OLS estimator under the Pitman nearness criterion can be extended to the case of the multivariatet error distribution when the specification error is not severe. It is also shown that the dominance of the SR estimator over the OLS estimator cannot be extended to the case of the multivariatet error distribution when the specification error is severe.
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页码:151 / 162
页数:11
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