Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known
AbstractWe consider the problem of estimating the first k coeffcients in a regression equation with k + 1 variables.For this problem with known variance of innovations, the neutral Laplace weighted-average least-squares estimator was introduced in Magnus (2002).We investigate properties of this estimator in the case where the unknown variance is estimated by least squares.We find that the optimality properties of the Laplace estimator only change marginally.Therefore we recommend the neutral Laplace estimator to be used in practice.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2002-77.
Date of creation: 2002
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Web page: http://center.uvt.nl
regression analysis; estimation; statistical distribution; variance;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
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- Giles, Judith A & Giles, David E A, 1993. " Pre-test Estimation and Testing in Econometrics: Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 7(2), pages 145-97, June.
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