Optimal decisions under combined prior ambiguity and likelihood misspecification coincide with those under correct specification for estimation and treatment assignment, regardless of misspecification degree.
Suppose that the decision-maker observes ad-dimensional signalx, posited to be drawn from a reference Gaussian likelihood,P θ,h(x)∼ N(I−1/2 θ h,I)
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You've Got to be Efficient: Ambiguity, Misspecification and Variational Preferences
Optimal decisions under combined prior ambiguity and likelihood misspecification coincide with those under correct specification for estimation and treatment assignment, regardless of misspecification degree.