Estimating Peer Effects Using Partial Network Data

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15 Avril 2020
Types de publication: 
Cahier de recherche
Vincent Boucher
Elysée Aristide Houndetoungan
Axe de recherche: 
Enjeux économiques et financiers
Social Networks
Peer effects
Missing variables
measurement errors
Classification JEL: 

We study the estimation of peer effects through social networks when researchers do not observe the entire network structure. Special cases include sampled networks, censored networks, misclassified links, and aggregated relational data. We assume that researchers can obtain a consistent estimator of the distribution of the network. We show that this assumption is sufficient for estimating peer effects using a linearin-means model. We provide an empirical application to the study of peer effects on students academic achievement using the widely used Add Health database and show that network data errors have a first-order downward bias on estimated peer effects.


Vincent Boucher : Department of Economics, Université Laval. CRREP. CREATE. CIRANO
Elysée Aristide Houndetoungan : Cy Cergy Paris Université and Thema.


We would like to thank Isaiah Andrews, Yann Bramoullé and Bernard Fortin for their helpful comments and insights, as always. We would also like to thank Eric Auerbach, Arnaud Dufays, Stephen Gordon, Chih-Sheng Hsieh, Arthur Lewbel, Tyler McCormick, Angelo Mele, Francesca Molinari, Onur Özgür, Eleonora Patacchini, Xun Tang, and Yves Zenou for helpful comments and discussions. Thank you also to the participants of the Applied/CDES seminar at Monash University, the Economic seminar at the Melbourne Business School, the Econometric workshop at the Chinese University of Hong Kong, and the Centre of Research in the Economics of Development workshop at the Université de Namur. This research uses data from Add Health, a program directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by Grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is given to Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain Add Health data files is available on the Add Health website ( No direct support was received from Grant P01-HD31921 for this research. An R package, including all replication codes is available at: