Empirical methods for networks data: social effects, network formation and measurement error
Arun Advani and
Bansi Malde ()
No W14/34, IFS Working Papers from Institute for Fiscal Studies
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 social networks. We begin by providing a common framework for 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 discuss identification of these models using both observational and experimental/quasi-experimental data. We then discuss models of network formation, drawing on a range of literatures to cover purely predictive models, reduced form models, and structural models, including those with a strategic element. Finally we discuss how one might collect data on networks, and the measurement error issues caused by sampling of networks, as well as measurement error more broadly.
Keywords: Networks; Social Eff ects; Peer Eff ects; Econometrics; Endogeneity; Measurement Error; Sampling Design (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-net, nep-soc and nep-ure
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