Bayesian Estimators As Voting Rules

We investigate the fairness of Bayesian estimators (BEs) by viewing them as (irresolute) voting rules and evaluating them by satisfaction of desirable social choice axioms. We characterize the class of BEs that satisfy neutrality by the class of BEs with neutral structures. We prove that a BE with a neutral structure is a minimax rule if it further satisfies parameter connectivity. We prove that no BE satisfies strict Condorcet criterion. We also propose three new BEs of natural frameworks and investigate their computational complexity and satisfaction of monotonicity and Condorcet criterion.

Authors

• Lirong Xia

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