Non‐Stationary Search and Assortative Matching
研究非平稳搜索匹配模型中分类匹配可能失败的条件，发现除了稳态条件外，更优个体需更不规避风险。
This paper studies assortative matching in a non‐stationary search‐and‐matching model with non‐transferable payoffs. Non‐stationarity entails that the number and characteristics of agents searching evolve endogenously over time. Assortative matching can fail in non‐stationary environments under conditions for which Morgan (1995) and Smith (2006) show that it occurs in the steady state. This is due to the risk of worsening match prospects inherent to non‐stationary environments. The main contribution of this paper is to derive the weakest sufficient conditions on payoffs for which matching is assortative. In addition to known steady state conditions, more desirable individuals must be less risk‐averse in the sense of Arrow–Pratt.