Identifying heterogeneous decision rules from choices when menus are unobserved

Consider aggregate choice data from a population with heterogeneity in both preferences (or more general decision rules) and in menus, and where the analyst has limited information about how menus are distributed across the population. We determine what can be inferred from aggregate data about the distribution of preferences by identifying the set of all distributions that are consistent with the preceding. Our main theorem strengthens and generalizes existing results on such identification and provides an alternative analytical approach (using convex capacities) to study the problem.

Authors

Institutions

Publication Details

Journal
Journal of Economic Behavior & Organization
Published
2026-10-13
DOI
https://doi.org/10.1016/j.jebo.2026.107801
Primary Topic
Decision-Making and Behavioral Economics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying heterogeneous decision rules from choices when menus are unobserved

Larry G. Epstein, Kaushil Patel
Journal of Economic Behavior & Organization
Decision-Making and Behavioral Economics
article

Identifying heterogeneous decision rules from choices when menus are unobserved

Larry G. Epstein, Kaushil Patel
article en

Abstract

Consider aggregate choice data from a population with heterogeneity in both preferences (or more general decision rules) and in menus, and where the analyst has limited information about how menus are distributed across the population. We determine what can be inferred from aggregate data about the distribution of preferences by identifying the set of all distributions that are consistent with the preceding. Our main theorem strengthens and generalizes existing results on such identification and provides an alternative analytical approach (using convex capacities) to study the problem.

Journal of Economic Behavior & OrganizationVol. 251
McGill University (CA)
Openalex Percentile: Top 6%
Decision-Making and Behavioral Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.