Sequential Learning under Informational Ambiguity
研究了在信息模糊环境下个体进行序贯社会学习的问题，发现即使只有少量模糊性，也可能引发信息级联和错误羊群行为，推翻了以往认为学习结果依赖环境细节的结论。
This paper investigates a sequential social learning problem in which individuals face ambiguity about others’ signal structures and have max-min expected utility preferences, thereby exhibiting ambiguity aversion. Unlike previous findings, which suggest that learning outcomes depend on the specifics of the learning environment, this study establishes information cascades as a robust outcome under ambiguity. With sufficient ambiguity, cascades arise almost surely, regardless of the statistical properties of signal structures. Moreover, standard results predicting the absence of cascades can easily break down: Even minimal ambiguity can trigger cascades when signals are bounded and lead to incorrect herding when signals are unbounded.