Errors in variables: consistent adjusted least squares (cals) estimation

DOI10.1080/03610928408828797zbMath0552.62055OpenAlexW1977058174MaRDI QIDQ3345623

Arie Kapteyn, Tom Wansbeek

Publication date: 1984

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928408828797

zbMATH Keywords

asymptotic distributionmaximum likelihoodlatent variablesmethod of momentsweighted regressionfunctional modelsidentifying restrictionsconsistent adjusted least squaressingle equation errors-in-variables model

Mathematics Subject Classification ID

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

Related Items (6)

Book review of: Tom Wansbeek and Erik Meijer, Measurement error and latent variables in econometrics ⋮ Estimation and testing when explanatory variables are endogenous. An application to a demand system ⋮ RECENTERED AND RESCALED INSTRUMENTAL VARIABLE ESTIMATION OF TOBIT AND PROBIT MODELS WITH ERRORS IN VARIABLES ⋮ Measurement error in a single regressor ⋮ FIML estimation of dynamic econometric systems from inconsistent data ⋮ On estimation and testing when explanatory variables are partly endogenous

Cites Work

• The commutation matrix: Some properties and applications
• Properties of some estimators for the errors-in-variables model
• Consistent estimation of a regression with errors in the variables
• The estimation of a multivariate linear relation
• Estimating structural and functional relationships
• Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
• Identification in the Linear Errors in Variables Model
• The vec-permutation matrix, the vec operator and Kronecker products: a review
• The Elimination Matrix: Some Lemmas and Applications
• Least-Squares versus Instrumental Variables Estimation in a Simple Errors in Variables Model
• Linear Statistical Inference and its Applications
• Consistent Estimates Based on Partially Consistent Observations
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