Methods to identify linear network models: a review

Arun Advani and Bansi Malde

Swiss Journal of Economics and Statistics, 2018, vol. 154, issue 1, 1-16

Abstract: 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.

Keywords: Networks; Social effects; Peer effects; Econometrics (search for similar items in EconPapers)
JEL-codes: C31 C81 Z13 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1186/s41937-017-0011-x Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sjecst:v:154:y:2018:i:1:d:10.1186_s41937-017-0011-x

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/41937

DOI: 10.1186/s41937-017-0011-x

Access Statistics for this article

Swiss Journal of Economics and Statistics is currently edited by Marius Brülhart

More articles in Swiss Journal of Economics and Statistics from Springer, Swiss Society of Economics and Statistics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().