Dynamic choice under ambiguity
This paper analyzes dynamic choice for ambiguity-sensitive decision makers. It demonstrates that unambiguous behavioral predictions can be obtained, even in the face of dynamic inconsistency, by taking the individual's preferences over decision trees, rather than acts, as primitive. In particular, it leverages preferences over trees to formalize Sophistication as an assumption about the way individuals resolve conflicts between preferences at different decision points. The main result employs Sophistication to provide a behavioral characterization of Consistent Planning (Strotz, 1956). The analysis accommodates arbitrary decision models and updating rules, and delivers unambiguous welfare comparisons. As an example, a characterization of prior-by-prior Bayesian updating and Consistent Planning for arbitrary maxmin-expected utility preferences is presented. The resulting sophisticated MEU preferences are then used to analyze the value of information under ambiguity; a basic trade-off between information acquisition and commitment is highlighted.
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