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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Official URL 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 |
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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: | Divisions > Division of Human and Social Sciences > School of Economics |
Depositing User: | Bansi Malde |
Date Deposited: | 17 Jan 2017 12:32 UTC |
Last Modified: | 15 Sep 2021 15:23 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/59894 (The current URI for this page, for reference purposes) |
Malde, Bansi: | ![]() |
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