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Methods to identify linear network models : a review
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Advani, Arun and Malde, Bansi (2018) Methods to identify linear network models : a review. Swiss Journal of Economics and Statistics, 154 (12). doi:10.1186/s41937-017-0011-x ISSN 0303-9692.
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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: | Journal Article | ||||||
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Subjects: | B Philosophy. Psychology. Religion > BF Psychology H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HM Sociology |
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Divisions: | Faculty of Social Sciences > Economics | ||||||
Library of Congress Subject Headings (LCSH): | Social influence, Social influence--Econometric models, Decision making, Decision making--Psychological aspects--Econometric models, Influence (Psychology)--Econometric models | ||||||
Journal or Publication Title: | Swiss Journal of Economics and Statistics | ||||||
Publisher: | Schweizerische Gesellschaft für Volkswirtschaft und Statistik | ||||||
ISSN: | 0303-9692 | ||||||
Official Date: | 5 February 2018 | ||||||
Dates: |
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Volume: | 154 | ||||||
Number: | 12 | ||||||
DOI: | 10.1186/s41937-017-0011-x | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Date of first compliant deposit: | 9 January 2018 | ||||||
Date of first compliant Open Access: | 9 February 2018 | ||||||
RIOXX Funder/Project Grant: |
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