Self-Confirming Equilibrium and Model Uncertainty
提出一种推广的非中性模糊态度下的自我确认均衡概念，发现模糊厌恶增强会扩大均衡集，因为已测试策略的收益分布被学习，而未测试策略的模糊性使它们吸引力下降，产生长期“现状偏见”。
We analyze a notion of self-confirming equilibrium with non-neutral ambiguity attitudes that generalizes the traditional concept. We show that the set of equilibria expands as ambiguity aversion increases. The intuition is quite simple: by playing the same strategy in a stationary environment, an agent learns the implied distribution of payoffs, but alternative strategies yield payoffs with unknown distributions; increased aversion to ambiguity makes such strategies less appealing. In sum, a kind of “status quo bias” emerges; in the long run, the uncertainty related to tested strategies disappears, but the uncertainty implied by the untested ones does not.