Marginal stochastic choice
Abstract
Models of stochastic choice typically use conditional choice probabilities given menus as the primitive for analysis, but in the field these are often hard to observe. We consider the case where an analyst has access to a marginal stochastic choice dataset containing the marginal distributions of available menus and of choices, but not to conditional choice frequencies. The Random Utility Model (RUM) has no testable implications for such datasets, but any restriction on the domain of feasible preference orders does limit the set of rationalizable marginals. The Luce model can also rationalize essentially any dataset, but unlike RUM its parameters can often be identified. We also demonstrate that additional testable implications for the marginals may arise when the distribution of menus is endogenous.
Fields of Study & Subjects
Economic and Environmental Valuation
Consumer Market Behavior and Pricing
Decision-Making and Behavioral Economics
Publication details
- Journal / source
- Theoretical Economics
- Publisher
- The Econometric Society
- Volume
- 21
- Issue
- 2
- Pages
- 373–401
- Publication date
- 1 January 2026
- Language
- EN