A note on the closed-form identification of regression models with a mismeasured binary regressor

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A note on the closed-form identification of regression models with a mismeasured binary regressor

Author Info

Chen, Xiaohong
Hu, Yingyao
Lewbel, Arthur

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Abstract

This note considers the identification of a nonparametric regression model with an unobserved 0-1 dichotomous regressor. The sample consists of a dependent variable and a 0-1 dichotomous proxy of the unobserved regressor. We obtain nonparametric identification of every element in the model as a closed-form function of the observed moments or densities. Our identification strategy does not require any additional sample information, such as instrumental variables or a secondary sample. The closed-form solution may be used to construct estimators of the unknowns.

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Article provided by Elsevier in its journal Statistics & Probability Letters.

Volume (Year): 78 (2008)
Issue (Month): 12 (September)
Pages: 1473-1479
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Handle: RePEc:eee:stapro:v:78:y:2008:i:12:p:1473-1479

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