The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation
提出源方法，通过区分不同不确定性来源并定义主观概率，将主观概率转化为下注意愿，从而定量分析不确定性，并在实验中让数据说话而不预设模糊态度。
We often deal with uncertain events for which no probabilities are known. Several normative models have been proposed. Descriptive studies have usually been qualitative, or they estimated ambiguity aversion through one single number. This paper introduces the source method, a tractable method for quantitatively analyzing uncertainty empirically. The theoretical key is the distinction between different sources of uncertainty, within which subjective (choice-based) probabilities can still be defined. Source functions convert those subjective probabilities into willingness to bet. We apply our method in an experiment, where we do not commit to particular ambiguity attitudes but let the data speak.