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Home Publications Empirical methods for networks data: social effects, network formation and measurement error

Empirical methods for networks data: social effects, network formation and measurement error

IFS Working Paper W14/34

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.

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Presentation
This presentation was delivered as part of the PEPA contribution to the 2012 ESRC Research Methods Festival.
IFS Working Paper
Co authored with Manuela Angelucci (Arizona) and Giacomo de Giorgi (Stanford)
Journal article | Journal of Public Economics
We present evidence on whether and how a household's behavior is influenced by the presence and characteristics of its extended family.
Presentation
This paper was presented at an internal IFS meeting on 11 Sept 2013.