Endogeneity in semiparametric binary response models
This paper develops and implements semiparametric methods for estimating binary response (binary choice) models withcontinuous endogenous regressors. It extends the existing literature on semiparametric estimation in single index binary response models to the case of endogenous regressors. It develops a control function approach to accounting for endogeneity in triangular and fully simulataneous binary response models. An application is given to the case of estimating the income effect in a labor market participation problem using a large micro data set from the British FES. The semiparametric estimator is found to perform well detecting a significant attenuation bias. The proposed estimator is contrasted to the corresponding Probit and Linear Probability specifications.
|Date of creation:||01 Jul 2001|
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- Richard Blundell & James L. Powell, 2001. "Endogeneity in nonparametric and semiparametric regression models," CeMMAP working papers CWP09/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Whitney K. Newey & James L. Powell & Francis Vella, 1999.
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- Arthur Lewbel & Linton, Oliver Linton, 1998. "Nonparametric Censored Regression," Cowles Foundation Discussion Papers 1186, Cowles Foundation for Research in Economics, Yale University. Full references (including those not matched with items on IDEAS)
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