依赖参照的效用理论
A Theory of Reference-Dependent Utility
AI总结：
本文提出弱秩依赖效用（WRDU）理论，刻画风险下内生参照依赖的偏好表示，其导数比率形式唯一容许，可产生Allais模式并阻断Rabin校准含义。
AI中文摘要：
本文刻画了一类在风险下具有内生参照依赖的、二阶连续可微的客观概率偏好表示。弱秩依赖效用（WRDU）保留客观概率，在一个内生参照点处分隔结果，并通过一个损益表示来评价彩票，其中参照点最大化一个惩罚泛函。一阶条件得到一个虚拟损失厌恶指数，等于损失域和收益域的边际效用之比，该指数同时包含了Köbberling和Wakker（2005）的基于效用的指数，以及Tversky和Kahneman（1992）的斜率比率作为特例。主定理表明，在满足仿射容许性、损失分解、分散单调性和衰减的一类偏好中，导数比率形式是唯一容许的。在该类中，WRDU在容许区域上产生Allais模式的典型形式，并通过依赖范围的衰减阻断Rabin校准含义。该结果是有条件的，并不主张在所有风险选择行为模型中具有唯一性。
英文摘要：
This paper characterizes a class of twice continuously differentiable objective-probability preference representations exhibiting endogenous reference dependence under risk. Weak rank-dependent utility (WRDU) preserves objective probabilities, partitions outcomes at an endogenous reference point, and evaluates lotteries through a gainloss representation in which the reference point maximizes a penalized functional. The first-order condition yields a virtual loss-aversion index equal to the ratio of marginal utilities across the loss and gain domains, recovering both the utility-based index of Köbberling and Wakker (2005) and the slope ratio of Tversky and Kahneman (1992) as special cases. The main theorem shows that, within a class satisfying affine admissibility, loss-factorization, dispersion monotonicity, and attenuation, the derivative-ratio form is uniquely admissible. In this class, WRDU generates the modal Allais pattern on an admissible region and blocks the Rabin calibration implication through range-dependent attenuation. The result is conditional and does not claim uniqueness over all behavioral models of risky choice.
