We examine the role of stochastic feasibility in consumer choice using a random conditional choice set rule (RCCSR) and uniquely characterize the model from conditions on stochastic choice data. Feasibility is modeled to permit correlation in availability of alternatives. This provides a natural way to examine substitutability/complementarity. We show that an RCCSR generalizes the random consideration set rule of [Manzini and Mariotti, 2014]. We then relate this model to existing literature. In particular, an RCCSR is not a random utility model.

This paper provides nonparametric identification results for a class of latent utility models with additively separable unobservable heterogeneity. These results apply to existing models of discrete choice, bundles, decisions under uncertainty, and matching. Under an independence assumption, such models admit a representative agent. As a result, we can identify how regressors alter the desirability of goods using only average demands. Moreover, average indirect utility (“welfare”) is identified without needing to specify or identify the distribution of unobservable heterogeneity.

Using a laboratory experiment, we identify whether decision-makers consider it a mistake to violate canonical choice axioms. To do this, we incentivize subjects to report axioms they want their decisions to satisfy. Then, subjects make lottery choices which might conflict with their axiom preferences. In instances of conflict, we give subjects the opportunity to re-evaluate their decisions. We find that many individuals want to follow canonical axioms and revise their choices to be consistent with the axioms. In a shorter online experiment, we show correlations of mistakes with response times and measures of cognition.