Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments
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Publication:1934886
DOI10.1016/j.econlet.2008.03.015zbMath1255.62111OpenAlexW2120290518MaRDI QIDQ1934886
Arthur Lewbel, Yingyao Hu, Xiaohong Chen
Publication date: 29 January 2013
Published in: Economics Letters (Search for Journal in Brave)
Full work available at URL: http://fmwww.bc.edu/EC-P/wp675.pdf
Related Items (10)
Generalized partially linear regression with misclassified data and an application to labour market transitions ⋮ Identification of additive and polynomial models of mismeasured regressors without instruments ⋮ Closed-form estimation of a regression model with a mismeasured binary regressor and heteroskedasticity ⋮ Reducing bias due to misclassified exposures using instrumental variables ⋮ Binary misclassification and identification in regression models ⋮ On the estimation of treatment effects with endogenous misreporting ⋮ Identifying the effect of a mis-classified, binary, endogenous regressor ⋮ Identification and estimation using heteroscedasticity without instruments: the binary endogenous regressor case ⋮ Nonparametric identification of a binary random factor in cross section data ⋮ Bounding the effect of a dichotomous regressor with arbitrary measurement errors
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- Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions
- Estimation of Nonlinear Models with Measurement Error
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