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Methods to Identify Linear Network Models: A Review

Advani, Arun, Malde, Bansi (2018) Methods to Identify Linear Network Models: A Review. Swiss Journal of Economics and Statistics, 154 (12). ISSN 0303-9692. (doi:10.1186/s41937-017-0011-x) (KAR id:59894)

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https://doi.org/10.1186/s41937-017-0011-x

Abstract

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.

Item Type: Article
DOI/Identification number: 10.1186/s41937-017-0011-x
Uncontrolled keywords: Networks, Social Effects, Peer Effects, Econometrics
Subjects: H Social Sciences
H Social Sciences > HN Social history and conditions. Social problems. Social reform
Divisions: Faculties > Social Sciences > School of Economics
Depositing User: Bansi Malde
Date Deposited: 17 Jan 2017 12:32 UTC
Last Modified: 06 Feb 2020 04:15 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/59894 (The current URI for this page, for reference purposes)
Malde, Bansi: https://orcid.org/0000-0003-1323-3383
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