Browsing by Subject "Kernel estimation"

Now showing 1 - 2 of 2
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    Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models
    (Center for Economic Research, Department of Economics, University of Minnesota, 1990-02) Lee, Lung-Fei
    This article provides a semi parametric method for the estimation of truncated regression models where the disturbances are independent with the regressors before truncation. This independency property provides useful information on the identification and estimation of the model. Our estimate is shown to be Vn-consistent and asymptotically normal. Consistent estimate of the asymptotic covariance matrix of the estimator is provided. Monte Carlo experiments are performed to investigate some finite sample properties of the estimator.
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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.