Identifying Behavioral Types

Christopher Kops, Paola Manzini, Marco Mariotti and Illia Pasichnichenko

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Abstract: We study identification in models of aggregate choice generated by unobserved behavioral types. An analyst observes only aggregate choice behavior, while the population distribution of types and their type-level choice patterns are latent. Assuming only minimal and purely qualitative prior knowledge of the process generating type-level choice probabilities, we characterize necessary and sufficient conditions for identifiability. Identification obtains if and only if the data exhibit sufficient cross-type behavioral heterogeneity, which we characterize equivalently through combinatorial matching conditions between types and alternatives, and through algebraic properties of the matrices mapping type-level to aggregate choice behavior.

Date: 2026-02
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