Browsing by Subject "Index model"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Efficient Semiparametric Scoring Estimation of Sample Selection Models
    (Center for Economic Research, Department of Economics, University of Minnesota, 1990-02) Lee, Lung-Fei
    A semi parametric profile likelihood method is proposed for estimation of sample selection models. The method is a two step scoring semi parametric estimation procedure based on index formulation and kernel density estimation. Under some regularity conditions, the estimator is asymptotically normal. This method can be applied to estimation of general sample selection models with multiple regimes and sequential choice models with selectivity. For the binary choice sample selection model, the estimator is asymptotically efficiency in the sense that its asymptotic variance matrix attains the asymptotic bound of G. Chamberlain.
  • Thumbnail Image
    Item
    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.