Adaptive partial policy innovation: coping with ambiguity through diversification
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. Study of the static minimax-regret criterion and its adaptive extension substantiate the theme. When the optimal policy is ambiguous, the static minimax-regret allocation always is fractional absent large fixed costs or deontological considerations. In dynamic choice problems, the adaptive minimax-regret criterion treats each cohort as well as possible, given the knowledge available at the time, and maximizes intertemporal learning about treatment response.
|Date of creation:||22 Apr 2008|
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- Charles F. Manski, 2006.
"Search Profiling With Partial Knowledge of Deterrence,"
Royal Economic Society, vol. 116(515), pages F385-F401, November.
- Charles F. Manski, 2005. "Search Profiling with Partial Knowledge of Deterrence," NBER Working Papers 11848, National Bureau of Economic Research, Inc.
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