Category-dependent preferences and stochastic choice

Bibliographic Data

ID11286162
AuthorsMatthew Ryan (0000-0003-4510-6514, Auckland University of Technology, corresponding author)
Year2026
Volume140
Pages102514
Publication date2026-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueMathematical Social Sciences (JOURNAL)
Journal identifiersISSN: 0165-4896 • E-ISSN: 1879-3118
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.mathsocsci.2026.102514
OpenAlexW7128075435
LanguageEN
References cited18

We introduce a generalisation of (Aguiar’s 2017) random categorisation rule (RCR) that relaxes (Aguiar’s 2017) Acyclicity axiom to an Asymmetry condition. Unlike other alternatives to the RCR, such as the models of Brady and Rehbeck (2016) and Cattaneo et al., (2020), our generalised random categorisation rule (GRCR) relaxes the linearity of preference, rather than varying the random consideration process. We show that the GRCR is also equivalent to allowing linear preferences to be category-dependent , with the requirement that the preferences associated with overlapping categories agree on the intersection. This allows the GRCR to capture intransitivities across categories, which may naturally arise when categorisation is used to frame choices. We provide a characterisation for the GRCR and compare it to the random utility model, as well as to the BR model, the RAM, and the model of Manzini and Mariotti (2014). • We relax transitivity of preferences in Aguiar’s (2017) random categorisation rule. • This is equivalent to allowing category-dependent linear preferences. • The generalised model captures a novel type of stochastic intransitivity. • We characterize the model and compare to alternatives

Axiom · Expected utility hypothesis · Frame (networking · Preference · Revealed preference · Stochastic modelling · Transitive relation · Type (biology · Decision-Making and Behavioral Economics · Epistemology, Ethics, and Metaphysics · Game Theory and Voting Systems

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