Stochastic sorting
研究了在不完全信息下，代理人基于可观测事前特征进行匹配的模型，推导了正向和负向排序的条件，并应用于风险分担和家庭收入不平等分析。
In many economic settings, matching takes place under imperfect information about agents’ characteristics that are payoff-relevant to the match. This paper develops a matching model in which agents’ payoff-relevant characteristics are realized after matching takes place, and matching is based on the agents’ observable ex-ante characteristics, which stochastically determine the payoff-relevant ones. We derive conditions for positive and negative sorting. The conditions differ depending on whether agents’ characteristics are stochastically larger or more variable as a function of the agents’ ex-ante attributes. We apply our framework to risk sharing and household income inequality.