网络中的同伴效应:一项调查

Y. Bramoullé, H. Djebbari, B. Fortin
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引用次数: 73

摘要

我们调查了最近快速增长的关于网络中同伴效应的文献。一个重要的反复出现的主题是,同伴效应的因果识别取决于网络本身的结构。在没有相关效应的情况下,即使在非线性、异构模型中,反射问题通常也由网络相互作用来解决。相比之下,微基础通常没有被识别。我们讨论和评估经济学家开发的各种方法,以解释相关效应和网络内生性。我们将这些方法分为四大类:随机同行、随机冲击、结构内生性和面板数据。我们回顾了一个新兴的文献放松假设,网络是完全已知的。在整个过程中,我们提供了现有文献的批判性阅读,并确定了未来研究的重要空白和方向。
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Peer Effects in Networks: A Survey
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 nonlinear, heterogeneous models. By contrast, microfoundations 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.
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