Browsing by Subject "Sample selection"

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    Semiparametric Instrumental Variable Estimation of Simultaneous Equation Sample Selection Models
    (Center for Economic Research, Department of Economics, University of Minnesota, 1991-06) Lee, Lung-Fei
    The identification and estimation of a semiparametric simultaneous equation model with selectivity have been considered. The identification of structural parameters from reduced form parameters in the semi parametric model requires stronger conditions than the usual rank condition in the classical simultaneous equation model or the parametric simultaneous equation sample selection model. The necessary order condition for identification in the semiparametric model corresponds to the over-identification condition in the classical model. Semiparametric two-stage estimation methods which generalize the two-stage least squares method and the generalized two-stage least squares method for the parametric model are introduced. The semi parametric generalized least squares estimator is shown to be asymptotically efficient in a class of semiparametric instrumental variable estimators.
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    Semiparametric Two Stage Estimation of Sample Selection Models Subject to Tobit-Type Selection Rules
    (Center for Economic Research, Department of Economics, University of Minnesota, 1990-07) Lee, Lung-Fei
    A semiparametric two stage estimation method is proposed for the estimation of sample selection models which are subject to Tobit-type selection rules. With randomization restrictions on the disturbances of the model, all the regression coefficients in the model are in general identifiable without exclusion restrictions. The proposed estimator is shown to be Vn-consistent and asymptotically normal. Some Monte Carlo results to demonstrate its finite sample performance are also provided.