This paper considers random coefficients binary choice models. The main goal is to estimate the density of the random coefficients nonparametrically. This is an ill-posed inverse problem characterized by an integral transform. A new density estimator for the random coefficients is developed,...

Nous considérons dans cet article des modèles à choix binaires et coefficients aléatoires. Le but est d'estimer de manière nonparamétrique la densité du coefficient aléatoire. Il s'agit d'un problème inverse mal posé caractérisé par une transformation intégrale. Un nouvel estimateur...

This paper considers random coefficients binary choice models. The main goal is to estimate the density of the random coefficients nonparametrically. This is an ill-posed inverse problem characterized by an integral transform. A new density estimator for the random coefficients is developed,...

In this paper we study nonparametric estimation in a binary treatment model where the outcome equation is of unrestricted form, and the selection equation contains multiple unobservables that enter through a nonparametric random coefficients specification. This specification is flexible because...