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Count Data Models with Heterogeneous Peer Effects under Rational Expectations

Aristide Houndetoungan

arXiv 27 May 2024 · Econometrics

arXiv:2405.17290 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper develops a peer effect model for count responses under rational expectations. The model accounts for heterogeneity in peer effects through groups based on observed characteristics. Identification is based on the linear model condition requiring friends' friends who are not direct friends, which I show extends to a broad class of nonlinear models. Parameters are estimated using a nested pseudo-likelihood approach. An empirical application on students' extracurricular participation reveals that females are more responsive to peers than males. An easy-to-use R package, CDatanet, is available for implementing the model.

Citation extraction

36
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88
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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
1Lee, Lung-fei and Li, Ji and Lin, Xu (2014) Binary choice models with social network under heterogeneous rational expectations1.00094100%
2Brock, William A and Durlauf, Steven N (2001) Discrete choice with social interactions1.00063100%
3Yang, Chao and Lee, Lung-fei (2017) Social interactions under incomplete information with heterogeneous expectations1.00063100%
4Guerra, José-Alberto and Mohnen, Myra (2022) Multinomial choice with social interactions: Occupations in Victorian London0.9416483%
5Blume, Lawrence E and Brock, William A and Durlauf, Steven N and Jay… (2015) Linear social interactions models0.87472100%
6Bramoullé, Yann and Djebbari, Habiba and Fortin, Bernard (2009) Identification of peer effects through social networks0.87462100%
7Aguirregabiria, Victor and Mira, Pedro (2007) Sequential estimation of dynamic discrete games0.8434375%
8Liu, Xiaodong and Zhou, Jiannan (2017) A social interaction model with ordered choices0.84333100%
9Xu, Xingbai and Lee, Lung-fei (2015) Maximum likelihood estimation of a spatial autoregressive Tobit model0.81142100%
10Calvó-Armengol, Antoni and Patacchini, Eleonora and Zenou, Yves (2009) Peer effects and social networks in education0.73732100%

Showing the top 10 of 36 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
1Quantile Peer Effect Models10pt10pt For comments and suggestions, I am grateful to Yann Bramoullé, Vincent Boucher, Firmin Doko Tchatoka, Mathieu Lambotte, and Marie Aurélie Lapierre. This research uses data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a program that is 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 US 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 (www.cpc.unc.edu/addhealth). No direct support was received from Grant P01-HD31921 for this research. An R package, including all replication codes, is available at: https://github.com/ahoundetoungan/QuantilePeer0.40511
2Heterogeneous Peer Effects with Endogenous Network Formation0.40511