The RLS Positive-Part Stein Estimator

Lee Adkins and Carter Hill

American Journal of Agricultural Economics, 1990, vol. 72, issue 3, 727-730

Abstract: The RLS Stein-rule estimator of the classical normal linear regression model is formed by taking a linear combination of the least squares and restricted least squares estimators. Using a simple analytical device, we prove that the convex combination known as the RLS positive-part Stein estimator dominates the conventional version under weighted quadratic loss. Possible uses for the positive-part estimator in economic and agricultural economic research are discussed.

Date: 1990
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:72:y:1990:i:3:p:727-730.

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