Bounding parameters in a linear regression model with a mismeasured regressor using additional information
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Publication:274905
DOI10.1016/j.jeconom.2005.03.009zbMath1345.62099OpenAlexW2040689793MaRDI QIDQ274905
Publication date: 25 April 2016
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jeconom.2005.03.009
Related Items (2)
Partial identification of probability distributions with misclassified data ⋮ Bounding the effect of a dichotomous regressor with arbitrary measurement errors
Cites Work
- Regressor diagnostics for the classical errors-in-variables model
- Bounding the effects of proxy variables on instrumental-variables coefficients
- Bounding the effects of measurement error in regressions involving dichotomous variables
- Bounding mean regressions when a binary regressor is mismeasured
- Instrumental variables estimation in errors-in-variables models when instruments are correlated with errors
- Errors in Variables in Linear Systems
- Consistent Sets of Estimates for Regressions with Errors in All Variables
- Restricting Regression Slopes in the Errors-in-Variables Model by Bounding the Error Correlation
- Bounding the Effects of Proxy Variables on Regression Coefficients
- Consistent Sets of Estimates for Regressions with Correlated or Uncorrelated Measurement Errors in Arbitrary Subsets of all Variables
- Sets of Posterior Means with Bounded Variance Priors
- Proper Posteriors from Improper Priors for an Unidentified Errors-in-Variables Model
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