The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Identification of peer effects through social networks
Open accessAbstract
We provide new results regarding the identification of peer effects. We consider an extended version of the linear-in-means model where each individual has his own specific reference group. Interactions are thus structured through a social network. We assume that correlated unobservables are either absent, or treated as fixed effects at the component level. In both cases, we provide easy-to-check necessary and sufficient conditions for identification. We show that endogenous and exogenous effects are generally identified under network interaction, although identification may fail for some particular structures. Monte Carlo simulations provide an analysis of the effects of some crucial characteristics of a network (i.e., density, intransitivity) on the estimates of social effects. Our approach generalizes a number of previous results due to Manski (1993), Moffitt (2001), and Lee (2006).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Learning about a New Technology: Pineapple in Ghana
Conley, T. G., & Udry, C. R. (2010) · American Economic Review · doi:10.1257/aer.100.1.35 · Cited by 2,180
Cited by
The Spread of Obesity in a Large Social Network over 32 Years
Christakis, N. A., & Fowler, J. H. (2007) · New England Journal of Medicine · doi:10.1056/nejmsa066082 · Cited by 5,007
Social contagion theory: examining dynamic social networks and human behavior
Christakis, N. A., & Fowler, J. H. (2013) · Statistics in Medicine · doi:10.1002/sim.5408 · Cited by 1,303
Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks
Aral, S., Muchnik, L., & Sundararajan, A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908800106 · Cited by 1,207
Homophily and contagion are generically confounded in observational social network studies
Shalizi, C. R., & Thomas, A. C. (2011) · Sociological Methods & Research · doi:10.1177/0049124111404820 · Cited by 994
“This idea has considerable plausibility and has been picked up by a number of other authors (Anagnostopoulos et al., 2008; Bramoullé et al., 2009), who have shown that it works as a test for direct influence in some models.”
BackgroundResultAral, S., & Walker, D. (2011) · Management Science · doi:10.1287/mnsc.1110.1421 · Cited by 786
Metadata
- Authors
- Bramoullé, Y., Djebbari, H., & Fortin, B.
- Venue
- Journal of Econometrics
- Publisher
- Elsevier BV
- Published
- 2009-05
- Volume
- 150
- Issue
- 1
- Pages
- 41-55
- ISSN
- 0304-4076 (ISSN-L)
- OpenAlex
- W3124288631
- Cited by
- 1,234
- References
- 1
- FWCI
- 34.44
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Identification of peer effects through social networks. https://app.cochat.ai/papers/10.1016/j.jeconom.2008.12.021
- The paper
- Bramoullé, Y., Djebbari, H., & Fortin, B. (2009). Identification of peer effects through social networks. Journal of Econometrics. https://doi.org/10.1016/j.jeconom.2008.12.021
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
