Category-dependent preferences and stochastic choice

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.

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Publication Details

Journal
Mathematical Social Sciences
Published
2026-02-05
DOI
https://doi.org/10.1016/j.mathsocsci.2026.102514
Primary Topic
Decision-Making and Behavioral Economics
Type
article
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article

Category-dependent preferences and stochastic choice

Mathematical Social Sciences
Decision-Making and Behavioral Economics
article

Category-dependent preferences and stochastic choice

article en

Abstract

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.

Mathematical Social SciencesVol. 140
Auckland University of Technology (NZ)
Reduced inequalities
Openalex Percentile: Top 64%
Decision-Making and Behavioral Economics
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Category-dependent preferences and stochastic choice · Mathematical Social Sciences (2026) | TGRS Research Map | TGRS