MAXIMUM LIKELIHOOD SOCIAL CHOICE RULE

This study is related to a Condorcetian problem of information aggregation that finds a true social ordering using individual orderings, that are supposed to partly contain the truth. In this problem, we introduce a new maximum likelihood rule and analyse its performance. This rule selects an alternative that maximizes the probability of realizing individual orderings, conditional on the alternative being the top according to a true social ordering. We show that under a neutrality condition of alternatives, the probability that our rule selects the true top alternative is higher than that of any other rule.