Good Samaritans in Networks: An Experiment on How Networks Influence Egalitarian Sharing and the Evolution of Inequality

The fact that the more resourceful people are sharing with the poor to mitigate inequality—egalitarian sharing—is well documented in the behavioral science research. How inequality evolves as a result of egalitarian sharing is determined by the structure of “who gives whom”. While most prior experimental research investigates allocation of resources in dyads and groups, the paper extends the research of egalitarian sharing to networks for a more generalized structure of social interaction. An agent-based model is proposed to predict how actors, linked in networks, share their incomes with neighbors. A laboratory experiment with human subjects further shows that income distributions evolve to different states in different network topologies. Inequality is significantly reduced in networks where the very rich and the very poor are connected so that income discrepancy is salient enough to motivate the rich to share their incomes with the poor. The study suggests that social networks make a difference in how egalitarian sharing influences the evolution of inequality.

行为科学研究已充分证实，资源禀赋更优的群体向穷人进行分享以缓解不平等——即平均主义分享（egalitarian sharing）——这一现象。平均主义分享所引发的不平等演化轨迹，取决于“谁向谁给予”的资源分配结构。尽管以往绝大多数实验研究均聚焦于二元组（dyads）与群体内部的资源分配问题，但本研究将平均主义分享的相关研究拓展至网络场景，以适配更具普适性的社会互动结构。本研究提出基于智能体的模型（agent-based model），用以预测网络中相互连接的行动者如何向邻接个体分享自身收入。后续开展的人类被试实验室实验进一步表明，不同网络拓扑结构（network topologies）下，收入分布会演化至不同的均衡状态。当极富群体与极贫群体直接相连时，收入差距会足够显著，足以激励富人向穷人进行分享，此时该网络中的不平等程度会得到显著降低。本研究证实，社会网络会对平均主义分享影响不平等演化的路径产生显著调节作用。