Choose for others as you would choose for yourself? A layered analysis of probabilistic preferential choice across social distances

The present study examines the effect of social distance on choice behavior through the lens of a probabilistic modeling framework. In an experiment, participants made incentive-compatible choices between lotteries in three different social distance conditions: self, friend, and stranger. We conduct a layered, within-subjects analysis that considers four properties of preferential choice. These properties vary in their granularity. At the coarsest level, we test whether choices are consistent with transitive underlying preferences. At a finer level of granularity, we evaluate whether each participant is best described as having fixed preferences with random errors or probabilistic preferences with error-free choices. In the latter case, we further distinguish three different bounds on response error rates. At the finest level, we identify the specific transitive preference ranking of the choice options that best describes a person’s choices. At each level of the analysis, we find that the stability between the self and friend conditions exceeds that between the self and stranger conditions. Stability increases with the coarseness of the analysis: Nearly all people are consistent with transitive preferences regardless of the social distance condition, but only for very few do we infer the same preference ranking in every social distance condition. Overall, while it matters whether one makes a choice on behalf of a friend versus for a stranger, the differences are most apparent when analyzing the data at a detailed level of granularity.

本研究通过一个概率建模框架来检验社会距离对选择行为的影响。在一项实验中，参与者在三种不同社会距离条件下（自己、朋友和陌生人）在彩票之间做出激励相容的选择。我们进行了一个分层的、被试内分析，考虑了偏好选择的四个特性。这些特性在其精细度上有所不同。在最粗略的层面上，我们测试选择是否与传递性的潜在偏好一致。在更精细的层面上，我们评估每个参与者是最好被描述为具有带有随机误差的固定偏好，还是具有无误差选择的概率偏好。在后一种情况下，我们进一步区分了反应误差率的三种不同界限。在最精细的层面上，我们确定最能描述一个人选择的选项的具体传递性偏好排序。在分析的每个层面上，我们发现自己和朋友条件之间的稳定性超过了自己和陌生人条件之间的稳定性。稳定性随着分析的粗略程度增加而增加：几乎所有人都与传递性偏好一致，无论社会距离条件如何，但只有极少数人我们能推断出在每个社会距离条件下都有相同的偏好排序。总体而言，虽然一个人是代表朋友还是代表陌生人做出选择是有影响的，但在精细层面分析数据时，差异最为明显。