Tabular Foundation Models and the Unity of Economic Behaviour

Abstract

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.