Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/323528 
Year of Publication: 
2025
Citation: 
[Journal:] Quantitative Marketing and Economics [ISSN:] 1573-711X [Volume:] 23 [Issue:] 1 [Publisher:] Springer US [Place:] New York, NY [Year:] 2025 [Pages:] 45-104
Publisher: 
Springer US, New York, NY
Abstract: 
Models derived from random utility theory represent the workhorse methods to learn about consumer preferences from discrete choice data. However, a large body of literature documents various behavioral patterns that cannot be captured by basic random utility models and require different non-unified adjustments to accommodate these patterns. In this article, we discuss strategies how to apply rational inattention theory—which explains a large variety of such departures—to the analysis of discrete choice among multiple alternatives described along multiple attributes. We first review existing applications that make restrictive belief assumptions to obtain choice probabilities in closed multinomial logit form. We then propose a model that allows for general consumer beliefs and demonstrate its empirical identification. Further, we illustrate how this model naturally motivates stylized empirical results that are hard to reconcile from a random utility perspective.
Subjects: 
Choice modeling
Rational inattention
Conjoint analysis
Discrete choice experiments
JEL: 
C00
C35
D83
M31
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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