Mixture Choice Data: Revealing Preferences and Cognition

• 成果类型: Article; Early Access
• 署名作者: Dardanoni, Valentino; Manzini, Paola; Mariotti, Marco; Petri, Henrik; Tyson, Christopher J.
• 署名单位: University of Palermo; University of Bristol; IZA Institute Labor Economics; University of London; Queen Mary University London; Deakin University; University of Bath
• 刊物名称: JOURNAL OF POLITICAL ECONOMY
• ISSN/ISSBN: 0022-3808
• DOI: 10.1086/721734
• 发表日期: 2023
• 关键词: identification; INFORMATION

摘要

Mixture choice data consist of the joint distribution of choices of a group of agents from a collection of menus, comprising the implied stochastic choice function plus any cross-menu correlations. When agents are heterogeneous with respect to both preferences and other aspects of cognition, we show that these two determinants of behavior are identified simultaneously by suitable mixture choice data. We also demonstrate how this finding can be extended to allow for specialized assumptions about cognition, focusing on models of random satisficing thresholds and quantal Fechnerian choice.