Regressor diagnostics for the classical errors-in-variables model
type: Item
instance of: scholarly article
title: Regressor diagnostics for the classical errors-in-variables model
zbMATH Open document ID: 0692.62058
DOI: 10.1016/0304-4076(88)90004-8
author: Steven Klepper
published in: Journal of Econometrics
publication date: 1988-01-01T00:00:00Z
review text: The author introduces the mixed linear model \(y=\beta 'X^*+\mu\) where the ``proxy variables'' \(X=X^*+\epsilon\) are subject to the measurement errors. A series of diagnostics are developed to prove the sensitivity of regression coefficient estimates to measurement errors in each regressor (large-sample-properties of the classical errors-in-variables model). Algorithms to compute the diagnostics are provided, and an example is used for illustrations.
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62J99
Mathematics Subject Classification ID: 62F12
Mathematics Subject Classification ID: 62P20
zbMATH DE Number: 4133342
zbMATH Keywords: mixed linear model
zbMATH Keywords: proxy variables
zbMATH Keywords: diagnostics
zbMATH Keywords: sensitivity of regression coefficient estimates to measurement errors
zbMATH Keywords: large-sample- properties
zbMATH Keywords: errors-in-variables model
zbMATH Keywords: Algorithms
reviewed by: Erik W. Grafarend
MaRDI profile type: Publication
full work available at URL: 0304-4076(88)90004-8
OpenAlex ID: W2066954221
cites work: Extending the Classical Normal Errors-in-Variables Model
cites work: Identification in the Linear Errors in Variables Model
cites work: Bounding the effects of measurement error in regressions involving dichotomous variables
cites work: Consistent Sets of Estimates for Regressions with Errors in All Variables
cites work: Q3339993
cites work: Errors in Variables in Linear Systems
cites work: Constraints Often Overlooked in Analyses of Simultaneous Equation Models
description: scientific article; zbMATH DE number 4133342