In a misspecified social learning setting, agents are condescending if they perceive their peers as having private information that is of lower quality than it is in reality. Applying this to a standard sequential model, we show that outcomes improve when agents are mildly condescending. In contrast, too much condescension leads to worse outcomes, as does anti-condescension.

翻译：在模型设定错误的社会学习环境中，若主体认为其同伴拥有的私有信息质量低于实际情况，则表现为屈尊态度。将该假设应用于标准序列模型，我们发现轻微屈尊态度会改善学习结果。相反，过度屈尊态度与反屈尊态度均会导致结果恶化。