In discrete choice models the marginal effect of a variable of interest that is interacted with another variable differs from the marginal effect of a variable that is not interacted with any variable. The magnitude of the interaction effect is also not equal to the marginal effect of the...

This paper is concerned with learning decision makers' (DMs) preferences using data on observed choices from a fi nite set of risky alternatives with monetary outcomes. We propose a discrete choice model with unobserved heterogeneity in consideration sets (the collection of alternatives...

A divide and conquer algorithm for exploiting policy function monotonicity is proposed and analyzed. To solve a discrete problem with n states and n choices, the algorithm requires at most nlog2(n)+5n objective function evaluations. In contrast, existing methods for nonconcave problems require...

I show that sharp identified sets in a large class of econometric models can be characterized by solving linear systems of equations. These linear systems determine whether, for a given value of a parameter of interest, there exists an admissible joint distribution of unobservables that can...

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...