Model misspecification is a serious issue since misspecification generally renders statistical inference invalid. However, specification testing of discrete choice models is rarely applied. This paper describes a nonparametric test procedure which uses a combination of smoothed residual plots...

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...

This paper establishes a general equivalence between discrete choice and rational inattention models. Matejka and McKay (2015) showed that when information costs are modelled using the Shannon entropy, the choice probabilities in the rational inattention (RI) model take the multinomial logit...

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...