A Characterisation of ‘Phelpsian’ Statistical Discrimination
证明，基于信号信息性和工人与任务匹配的统计歧视，当且仅当无法从技能的经验分布唯一识别雇主观察到的信号结构时才有可能；歧视不存在等价于存在公平的、依赖技能的薪酬，并连接了统计歧视与贝叶斯说服理论。
Abstract We establish that a type of statistical discrimination—that based on informativeness of signals about workers’ skills and the ability appropriately to match workers to tasks—is possible if and only if it is impossible uniquely to identify the signal structure observed by an employer from a realised empirical distribution of skills. The impossibility of statistical discrimination is shown to be equivalent to the existence of a fair, skill-dependent, remuneration for workers. Finally, we connect the statistical discrimination literature to Bayesian persuasion, establishing that if discrimination is absent, then the optimal signalling problem results in a linear pay-off function (as well as a kind of converse).