摘要:We provide a characterization of virtual Bayesian implementation in
pure strategies for environments satisfying no-total-indifference. A social choice
function in such environments is virtually Bayesian implementable if and only if it
satisfies incentive compatibility and a condition we term virtual monotonicity. The
latter is weaker than Bayesian monotonicity - known to be necessary for Bayesian
implementation. Virtual monotonicity is weak in the sense that it is generically
satisfied in environments with at least three alternatives. This implies that in
most environments virtual Bayesian implementation is as successful as it can be
(incentive compatibility is the only condition needed).