Proxies versus omitted variables in regression analysis

DOI10.1016/0024-3795(94)00591-5zbMath0843.62067OpenAlexW2152052597MaRDI QIDQ1914235

Tom Wansbeek, Paul A. Bekker

Publication date: 21 August 1996

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0024-3795(94)00591-5

zbMATH Keywords

metricmeasurement errorinconsistencyordinary least squares

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Miscellaneous inequalities involving matrices (15A45) Basic linear algebra (15A99)

Cites Work

• Unnamed Item
• The positive semidefiniteness of partitioned matrices
• Schur complements and statistics
• MSE dominance of least squares with errors-of-observation
• Consistent Sets of Estimates for Regressions with Errors in All Variables
• Comment on Identification in the Linear Errors in Variables Model
• Consistent Sets of Estimates for Regressions with Correlated or Uncorrelated Measurement Errors in Arbitrary Subsets of all Variables
• On Deriving the Inverse of a Sum of Matrices
• Extending the Classical Normal Errors-in-Variables Model
• Specification Error Analysis with Stochastic Regressors
• Relative Asymptotic Bias from Errors of Omission and Measurement
• A Note on the Use of Proxy Variables

This page was built for publication: Proxies versus omitted variables in regression analysis