Parameter-Free Elicitation of Utility and Probability Weighting Functions
提出一种无参数两步法，在等级依赖期望效用理论和累积前景理论下依次引出效用函数和决策权重，无需预设参数形式，并通过实验获得个体在收益和损失域的效用与概率权重函数。
This paper proposes a two-step method to successively elicit utility functions and decision weights under rank-dependent expected utility theory and its “more descriptive” version: cumulative prospect theory. The novelty of the method is that it is parameter-free, and thus elicits the whole individual preference functional without imposing any prior restriction. This method is used in an experimental study to elicit individual utility and probability weighting functions for monetary outcomes in the gain and loss domains. Concave utility functions are obtained for gains and convex utility functions for losses. The elicited weighting functions satisfy upper and lower subadditivity and are consistent with previous parametric estimations. The data also show that the probability weighting function for losses is more “elevated” than for gains.