Some Applications of Semi-Nonparametric Maximum Likelihood Estimation

Bas van der Klaauw
Ruud H. Koning

October 1996

An alternative to estimation of microeconometric models under the assumption of normality of the distribution of the disturbances is semi-nonparametric maximum likelihood estimation. In a particular class of this kind of models, the density function of the disturbances is approximated by a Hermite series. In this paper we will discuss this approach in the context of a popular microeconometric model (the sample selection model) and we apply the model to a truncated switching regression model with endogenous regimes. A new choice of base functions of the Hermite series is presented and the semi-nonparametric approach is used to examine sensitivity to the assumption of normality of estimation results of a model for rent assistance and housing demand in Koning (1995).

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Last updated: May 29, 1998.