AI 中文总结
本研究通过统一选择实验，用冻结的表格型基础模型恢复决策者隐藏选择，再估计随机效用模型，构建出适用于所有经济行为领域的统一模型，提升了选择预测效果。
AI 中文摘要
经济学针对风险、时间、损失、估值及社会选择分别采用不同的行为模型。本研究开展一项统一选择实验，让同一批决策者面对所有这些领域。隐藏某一决策者在某一领域的选择，要求冻结的表格型基础模型从该决策者其他领域的选择及其他参与者的标记选择中恢复该隐藏选择。该基础模型的表现优于训练样本中位数，若将可见选择在不同决策者间打乱，其增益便会消失。随后，在该基础模型学习到的表征上估计一个随机效用模型，此结构模型在所有领域采用相同的效用函数，保留了基础模型降低的大部分预测误差，可预测效用估计中未包含的领域，还能复现不同人群间行为指标的共变关系。所得模型分离出三类对象：一个学习到的共同选择域、该域上的一个系统性效用函数，以及一个在观测菜单上生成随机选择的随机成分。
英文摘要
Economics uses different behavioural models for risk, time, losses, valuation, and social choice. I study a unified choice experiment in which the same decision makers face all these domains. I hide a decision maker's choices in one domain and ask a frozen tabular foundation model to recover them from that decision maker's choices elsewhere and labelled choices by other participants. The foundation model improves on the training-sample median, and the gain disappears when visible choices are shuffled across decision makers. I then estimate one random-utility model over the foundation model's learned representation. This structural model applies the same utility function in every domain, retains most of the foundation model's reduction in prediction error, predicts domains excluded from utility estimation, and reproduces how behavioural measures co-move across people. The resulting model separates three objects: a learned common choice domain, one systematic utility function on that domain, and one random component that generates stochastic choice on observed menus.
Comments56 pages, 4 figures, and 19 tables, including the appendix
