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

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.
Year of publication:
2014
Authors: Advani, Arun ; Malde, Bansi
Publisher: London : Institute for Fiscal Studies (IFS)
Subject: Networks | Social Effects | Peer Effects | Econometrics | Endogeneity | Measurement Error | Sampling Design
Series:
Type of publication: Book / Working Paper
Type of publication (narrower categories): Working Paper
Language: English
Other identifiers:
10.1920/wp.ifs.2014.1434 [DOI]
815366477 [GVK]
hdl:10419/119552 [Handle]
Classification: C31 - Cross-Sectional Models; Spatial Models ; C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data ; Z13 - Social Norms and Social Capital
Source:
Persistent link: https://ebvufind01.dmz1.zbw.eu/10011335608
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