A Note on the Use of Proxy Variables

DOI10.2307/1912971zbMath0258.62066OpenAlexW2025019873MaRDI QIDQ5674270

Michael Wickens

Publication date: 1972

Published in: Econometrica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/1912971

Mathematics Subject Classification ID

Applications of statistics to economics (62P20)

Related Items (21)

Proxies versus omitted variables in regression analysis ⋮ Assessing consumer demand with noisy neural measurements ⋮ Dropping variables versus use of proxy variables in linear regression ⋮ A note on the use of a proxy variable in testing hypothesis ⋮ On the use of a proxy variable in the test for homoscedasticity ⋮ The exact distribution and density functions of a pre-test estimator of the error variance in a linear regression model with proxy variables ⋮ A note on bias from proxy variables with systematic errors ⋮ Expected MSE of errors-in-variables and omitted variables models ⋮ The effects of the proxy information on the iterative Stein-rule estimator of the disturbance variance ⋮ Investigating omitted variable bias in regression parameter estimation: a genetic algorithm approach ⋮ Superiority comparisons of heterogeneous linear estimators ⋮ MSE dominance of least squares with errors-of-observation ⋮ The role of proxy information in missing data analysis ⋮ Comparison of the Iterative Stein-Rule and the Usual Estimators of the Disturbance Variance Under the Pitman Nearness Criterion in a Linear Regression Model with Proxy Variables ⋮ PMSE performance of the Stein-rule and positive-part Stein-rule estimators in a regression model with or without proxy variables ⋮ Properties of the ordinary least squares and stein-rule predictions in linear regression models with proxy variables ⋮ PMSE dominance of the positive-part shrinkage estimator in a regression model with proxy variables ⋮ Testing linear restrictions on coefficients in a linear regression model with proxy variables and spherically symmetric disturbances ⋮ Inflation of Type I error rate in multiple regression when independent variables are measured with error ⋮ Some sampling properties of the two-stage test in a linear regression with a proxy variable ⋮ The relevance of large sample properties of estimators for the errors-in-variables model:a monte carlo study

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