We survey the recent, fast-growing literature on peer effects in networks. An important recurring theme is that the causal identification of peer effects depends on the structure of the network itself. In the absence of correlated effects, the reflection problem is generally solved by network interactions even in non-linear, heterogeneous models. By contrast, microfounda-tions are generally not identified. We discuss and assess the various approaches developed by economists to account for correlated effects and network endogeneity in particular. We classify these approaches in four broad categories: random peers, random shocks, structural endogeneity and panel data. We review an emerging literature relaxing the assumption that the network is perfectly known. Throughout, we provide a critical reading of the existing literature and identify important gaps and directions for future research.

中文翻译：

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网络中的对等效应：一项调查

我们调查了有关网络对等效应的最新，增长迅速的文献。一个反复出现的重要主题是，对等效应的因果关系识别取决于网络本身的结构。在没有相关影响的情况下，即使在非线性异构模型中，反射问题通常也可以通过网络交互来解决。相比之下，通常无法识别微观基础。我们讨论和评估经济学家开发的各种方法，以解决相关影响，尤其是网络内生性。我们将这些方法分为四大类：随机同伴，随机冲击，结构内生性和面板数据。我们回顾了新兴的文献，放松了网络是众所周知的假设。始终，