标题： 分位数同伴效应模型 显示英文标题

标题： Quantile Peer Effect Models

摘要： 我提出了一种灵活的结构模型来估计同伴效应在整个同伴结果分布的不同分位数上的影响。 该模型允许具有低、中等和高结果的同伴施加不同的影响，从而比基于总体度量的标准方法捕捉到更细微的同伴效应模式。 我证明了纳什均衡的存在性和唯一性，并展示了模型参数可以使用简单的工具变量策略进行估计。 将该模型应用于文献中常见的多种结果，我发现了一系列多样且丰富的同伴影响模式，这些模式挑战了标准模型中的内在假设。 这些发现具有重要的政策含义：网络中的关键人物地位不仅取决于网络结构，还取决于人口内结果的分布。 显示英文摘要

摘要： I propose a flexible structural model to estimate peer effects across various quantiles of the peer outcome distribution. The model allows peers with low, intermediate, and high outcomes to exert distinct influences, thereby capturing more nuanced patterns of peer effects than standard approaches that are based on aggregate measures. I establish the existence and uniqueness of the Nash equilibrium and demonstrate that the model parameters can be estimated using a straightforward instrumental variable strategy. Applying the model to a range of outcomes that are commonly studied in the literature, I uncover diverse and rich patterns of peer influences that challenge assumptions inherent in standard models. These findings carry important policy implications: key player status in a network depends not only on network structure, but also on the distribution of outcomes within the population.