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文章基本信息

  • 标题:Methods to identify linear network models: a review
  • 本地全文:下载
  • 作者:Arun Advani ; Bansi Malde
  • 期刊名称:Swiss Journal of Economics and Statistics
  • 出版年度:2018
  • 卷号:154
  • 期号:1
  • 页码:1-16
  • DOI:10.1186/s41937-017-0011-x
  • 摘要:In many contexts we may be interested in understanding whether direct connections between agents, such as declared friendships in a classroom or family links in a rural village, affect their outcomes. In this paper, we review the literature studying econometric methods for the analysis of linear models of social effects , a class that includes the ‘linear-in-means’ local average model, the local aggregate model, and models where network statistics affect outcomes. We provide an overview of the underlying theoretical models, before discussing conditions for identification using observational and experimental/quasi-experimental data.
  • 关键词:Networks; Social effects; Peer effects; Econometrics; C31; C81; Z13
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