Distribution-free estimation of the random coefficient dummy endogenous variable model

This paper considers the estimation of the random coefficient dummy endogenous variable model under a symmetry and index condition for the error distribution. We follow a two-step approach.The selection equation is estimated first; in the second step an instrumental variables estimator is proposed for the ourcome equation through a pairwise comparison method. Our approach can be readily extended to the general switching regression model. In constrast to the existing literature on sample selection models, the exclusion restriction is not needed here for model identification; furthermore, the intercept term for the outcome equation can be estimated at the usual parametric rate.