We study a variant of a random utility model that takes a probability distribution over preference relations as its primitive. We do not model products using a space of observed characteristics. The distribution of preferences is only partially identified using cross-sectional data on varying...

We study a variant of a random utility model that takes a probability distribution over preference relations as its primitive. We do not model products using a space of observed characteristics. The distribution of preferences is only partially identified using cross-sectional data on varying...

We study the nonparametric identification of distributions of utility functions in a multiple purchase setting with a finite number of consumers. Each utility function takes as arguments subsets or, alternatively, quantities of the multiple goods. We exploit mathematical insights from auction...

We propose a simple nonparametric mixtures estimator for recovering the joint distribution of parameter heterogeneity in economic models, such as the random coefficients logit. The estimator is based on linear regression subject to linear inequality constraints, and is robust, easy to program...

The random coefficients, multinomial choice logit model has been widely used in empirical choice analysis for the last 30 years. We are the first to prove that the distribution of random coefficients in this model is nonparametrically identified. Our approach exploits the structure of the logit...