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....

This paper extends my research applying statistical decision theory to treatment choice with sample data, using maximum regret to evaluate the performance of treatment rules. The specific new contribution is to study as-if optimization using estimates of illness probabilities in clinical choice...

We show how to bound the effect of belief-dependent preferences on choices in sequential two-player games without information about the (higher-order) beliefs of players. The approach can be applied to a class of belief-dependent preferences which includes reciprocity (Dufwenberg and...

We combine the choice data of proposers and responders in the ultimatum game, their expectations elicited in the form of subjective probability questions, and the choice data of proposers ("dictators") in a dictator game to estimate a structural model of decision making under uncertainty. We use...

We show how to bound the effect of belief-dependent preferences on choices in sequential two-player games without information about the (higher-order) beliefs of players. The approach can be applied to a class of belief-dependent preferences which includes reciprocity (Dufwenberg and...

We derive bounds on the causal effect of belief-dependent preferences (reciprocity and guilt aversion) on choices in sequential two-player games without exploiting information or data on the (higher-order) beliefs of players. We show how informative bounds can be derived by exploiting a specific...

We derive bounds on the causal effect of belief-dependent preferences (reciprocity and guilt aversion) on choices in sequential two-player games without exploiting information or data on the (higher-order) beliefs of players. We show how informative bounds can be derived by exploiting a specific...