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Endogenous Selection Or Treatment Model Estimation

  • Arthur Lewbel

    ()

    (Boston College)

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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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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  4. Arthur Lewbel, 1998. "Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors," Econometrica, Econometric Society, vol. 66(1), pages 105-122, January.
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  6. Denis Cogneau & Eric Maurin, 2001. "Parental Income and School Attendance in a Low-Income Country : A semi-parametric analysis," Working Papers DT/2001/16, DIAL (Développement, Institutions et Mondialisation).
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  10. Chen, Songnian & Lee, Lung-Fei, 1998. "Efficient Semiparametric Scoring Estimation Of Sample Selection Models," Econometric Theory, Cambridge University Press, vol. 14(04), pages 423-462, August.
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