This article introduces a multinomial logit model that uses ancillary information to control for uncertainty in both the observed choices made by respondents, and in the attributes of a respondent's choice set. Simulated data are used to compare the performance of this estimator versus simpler...

This article introduces a multinomial logit model that uses ancillary information to control for uncertainty in both the observed choices made by respondents, and in the attributes of a respondent's choice set. Simulated data are used to compare the performance of this estimator versus simpler...

This paper analyzes the interaction of direct and indirect risk selection in health insurance markets. It is shown that direct risk selection - using measures unrelated to the benefit package like selective advertising or 'losing' applications of high risk individuals - nevertheless has an...

This paper analyzes the distortions of health insurers' benefit packages due to adverse selection when there is imperfect competition. Within a discrete choice setting with two risk types, the following main results are derived: For intermediate levels of competition, the benefit packages of...

We establish nonparametric identification in a class of so-called index models using a novel approach that relies on general topological results. Our proof strategy imposes very weak smoothness conditions on the functions to be identified and does not require any large support conditions on the...