AN EFFICIENT METHOD OF MOMENTS ESTIMATOR FOR DISCRETE CHOICE MODELS WITH CHOICE-BASED SAMPLING

In this paper a new estimator is proposed for discrete choice models with choice-based sampling. The estimator is efficient and can incorporate information on the marginal choice probabilities in a straightforward manner and for that case leads to a procedure that is computationally and intuitively more appealing than the estimators that have been proposed before. The idea is to start with a flexible parameterization of the distribution of the explanatory variables and then rewrite the estimator to remove dependence on these parametric assumptions.