Dropping variables versus use of proxy variables in linear regression

DOI10.1016/0378-3758(95)00045-3zbMath0849.62035OpenAlexW2074174848WikidataQ29038440 ScholiaQ29038440MaRDI QIDQ1918145

Peter Stahlecker, Götz Trenkler

Publication date: 18 July 1996

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(95)00045-3

zbMATH Keywords

least squares estimatorproxiesproxy variablesdropping variablesmatrix mean square error criterionmatrix superiority

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Admissibility in statistical decision theory (62C15)

Related Items (4)

The effects of the proxy information on the iterative Stein-rule estimator of the disturbance variance ⋮ The role of proxy information in missing data analysis ⋮ PMSE performance of the Stein-rule and positive-part Stein-rule estimators in a regression model with or without proxy variables ⋮ PMSE dominance of the positive-part shrinkage estimator in a regression model with proxy variables

Cites Work

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• Nonnegative and positive definiteness of matrices modified by two matrices of rank one
• Recursive estimation in econometrics
• Admissible linear estimators in restricted linear models
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• MSE dominance of least squares with errors-of-observation
• A Test of the Mean Square Error Criterion for Restrictions in Linear Regression
• Relative Asymptotic Bias from Errors of Omission and Measurement
• A Note on the Use of Proxy Variables
• Conditions for Positive and Nonnegative Definiteness in Terms of Pseudoinverses

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