Estimation of regression coefficients after a preliminary test for homoscedasticity

DOI10.1016/0304-4076(80)90003-2zbMath0425.62052OpenAlexW2049280501MaRDI QIDQ1135593

Toshihisa Toyoda, Kazuhiro Ohtani

Publication date: 1980

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(80)90003-2

zbMATH Keywords

preliminary testhomoscedasticityestimation of regression coefficientsmean square error of pre-test estimatororthogonal regressors

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Linear regression; mixed models (62J05)

Related Items (11)

The density function and the MSE dominance of the pre-test estimator in a heteroscedastic linear regression model with omitted variables ⋮ Measuring the degree of severity of heteroskedasticity and the choice between the ols estimator and the 2sae ⋮ Testing linear hypothesis on regression coefficients after a pre-test for disturbance variance ⋮ The exact risk performance of a pre-test estimator in a heteroskedastic linear regression model under the balanced loss function ⋮ On estimating the common mean in two normal distributions after a preliminary test for equality of variances ⋮ Some improved estimators in the case of possible heteroscedasticity ⋮ Some risk results for a two-stage pre-test estimator in the case of possible heteroskedasticity ⋮ Minimax estimation of common coefficients of several regression models under quadratic loss ⋮ Estimation of the common location paeameters for the two linear models ⋮ Weighted-Average Least Squares Prediction ⋮ Optimal critical values of pre-tests when estimating the regression error variance: Analytical findings under a general loss structure

Cites Work

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• Estimation of variance after a preliminary test of homogeneity and optimal levels of significance for the pre-test
• On choosing the optimal level of significance for the Durbin-Watson test and the Bayesian alternative
• Allocation in Stratified Sampling Subsequent to Preliminary Test of Significance
• Optimal Critical Values for Pre-Testing in Regression
• The Heteroscedastic Linear Model: Exact Finite Sample Results
• Minimax Regret Significance Points for a Preliminary Test in Regression Analysis
• Combinations of Unbiased Estimators of the Mean which Consider Inequality of Unknown Variances
• Weaker Criteria and Tests for Linear Restrictions in Regression

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