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Estimation From Transformed Data Under the Linear Regression Model

Erkki P. Liski, Götz Trenkler, Jürgen Groß

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Abstract

The results of Stahlecker and Schmidt (1987) are considered for a more general class of transformations of the dependent variable. Mean square error matrix dominance of the so-called naive estimator over the usual OLS estimator is investigated and the related testing procedures are discussed. Some remarks on the admissibility of the naive estimator are given.

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What this paper is about

The results of Stahlecker and Schmidt (1987) are considered for a more general class of transformations of the dependent variable. Mean square error matrix dominance of the so-called naive estimator over the usual OLS estimator is investigated and the related testing procedures are discussed. Some remarks on the admissibility of the naive estimator are given.

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Available abstract

The results of Stahlecker and Schmidt (1987) are considered for a more general class of transformations of the dependent variable. Mean square error matrix dominance of the so-called naive estimator over the usual OLS estimator is investigated and the related testing procedures are discussed. Some remarks on the admissibility of the naive estimator are given.

Key concepts: Mathematics, Estimator, Statistics, Mean squared error, Efficient estimator, Linear regression, Ordinary least squares, Class (philosophy)

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