Center for Economic Research, Department of Economics, University of Minnesota
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.
Lee, L., (1990), "Efficient Semiparametric Scoring Estimation of Sample Selection Models", Discussion Paper No. 255, Center for Economic Research, Department of Economics, University of Minnesota.
Efficient Semiparametric Scoring Estimation of Sample Selection Models.
Center for Economic Research, Department of Economics, University of Minnesota.
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