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Quantile Peer Effect Models

Aristide Houndetoungan

arXiv 15 Jun 2025 · Econometrics

arXiv:2506.12920 · PDF · DOI · OpenAlex · Extracted main text

Abstract

I propose a flexible structural model to estimate peer effects across various quantiles of the peer outcome distribution. The model allows peers with low, intermediate, and high outcomes to exert distinct influences, thereby capturing more nuanced patterns of peer effects than standard approaches that are based on aggregate measures. I establish the existence and uniqueness of the Nash equilibrium and demonstrate that the model parameters can be estimated using a straightforward instrumental variable strategy. Applying the model to a range of outcomes that are commonly studied in the literature, I uncover diverse and rich patterns of peer influences that challenge assumptions inherent in standard models. These findings carry important policy implications: key player status in a network depends not only on network structure, but also on the distribution of outcomes within the population.

Citation extraction

38
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68
in-text mentions
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distinct cited
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Boucher, V., M. Rendall, P. Ushchev, and Y. Zenou (2024) Toward a general theory of peer effects1.000116100%
2Ballester, C., A. Calvó-Armengol, and Y. Zenou (2006) Who's who in networks0.92843100%
3Blume, L. E., W. A. Brock, S. N. Durlauf, and R. Jayaraman (2015) Linear social interactions models0.92843100%
4Bramoullé, Y., H. Djebbari, and B. Fortin (2009) Identification of peer effects through social networks0.73732100%
5Tao, J. and L.-f. Lee (2014) A social interaction model with an extreme order statistic0.73732100%
6Tatsi, E (2015) Endogenous Social Interactions: Which Peers Matter? in0.73732100%
7Bramoullé, Y., H. Djebbari, and B. Fortin (2020) Peer effects in networks: A survey0.64422100%
8Lee, L.-F., X. Liu, E. Patacchini, and Y. Zenou (2021) Who is the key player? A network analysis of juvenile delinquency0.64422100%
9Herstad, E. I. and M. Shin (2025) Identification of a rank-dependent peer effect model0.58531100%
10Hyndman, R. J. and Y. Fan (1996) Sample quantiles in statistical packages0.5112250%

Showing the top 10 of 38 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Heterogeneity in peer effects for binary outcomes0.40511