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Endogenous Selection Or Treatment Model Estimation

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  • Arthur Lewbel

    ()
    (Boston College)

Abstract

In a sample selection or treatment effects model, common unobservables may affect both the outcome and the probability of selection in unknown ways. This paper shows that the distribution function of potential outcomes, conditional on covariates, can be identified given an observed variable V that affects the treatment or selection probability in certain ways and is conditionally independent of the error terms in a model of potential outcomes. Selection model estimators based on this identification are provided, which take the form of simple weighted averages, GMM, or two stage least squares. These estimators permit endogenous and mismeasured regressors. Empirical applications are provided to estimation of a firm investment model and schooling effects on wages model.

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Bibliographic Info

Paper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 462.

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Length: 44 pages
Date of creation: 01 Jun 2000
Date of revision: 13 Jun 2007
Handle: RePEc:boc:bocoec:462

Note: This paper was previously titled "Selection Model and Conditional Treatment Effects, Including Endogenous Regressors"
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Keywords: sample selection; threshold; censoring; semiparametric; endogenous; instrumental variables; switching regression; average treatment effects; heteroskedasticity; latent variable models;

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