We argue that comprehensive out-of-sample (OOS) evaluation using statistical decision theory (SDT) should replace the current practice of K-fold and Common Task Framework validation in machine learning (ML) research. SDT provides a formal framework for performing comprehensive OOS evaluation...

This paper develops a broad theme about policy choice under ambiguity through study of a particular decision criterion. The broad theme is that, where feasible, choice between a status quo policy and an innovation is better framed as selection of a treatment allocation than as a binary decision....

"Research on collective provision of private goods has focused on distributional considerations. This paper studies a class of problems of decision under uncertainty in which the argument for collective choice emerges from the mathematics of aggregating individual payoffs. Consider decision...