Three Layers of Uncertainty
将不确定性分解为风险、模型模糊和模型误设三个层次，通过新实验设计分别测量人们对各层次的态度，发现三个层次在行为上可区分，并首次提供模型误设在不确定性决策中作用的实证证据。
Abstract We explore decision-making under uncertainty using a framework that decomposes uncertainty into three distinct layers: (1) risk, which entails inherent randomness within a given probability model; (2) model ambiguity, which entails uncertainty about the probability model to be used; and (3) model misspecification, which entails uncertainty about the presence of the correct probability model among the set of models considered. Using a new experimental design, we isolate and measure attitudes toward each layer separately. We conduct our experiment on three different subject pools and document the existence of a behavioral distinction between the three layers. In addition to providing new insights into the underlying processes behind ambiguity aversion, we provide the first empirical evidence of the role of model misspecification in decision-making under uncertainty.