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Count Data Models With Heterogeneous Peer Effects Under Rational Expectations

Aristide Houndetoungan

Journal of Applied Econometrics2026https://doi.org/10.1002/jae.70045article
AJG 3ABDC A*
Weight
0.50

Abstract

This paper develops a peer effect model for count responses under rational expectations. The model accounts for heterogeneity in peer effects across groups based on observed characteristics. Identification is based on the linear model condition that requires the presence of friends of friends who are not direct friends. I show that this identification condition extends to a broad class of nonlinear models. Parameters are estimated using a nested pseudo‐likelihood approach. An empirical application to 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.

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https://doi.org/https://doi.org/10.1002/jae.70045

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@article{aristide2026,
  title        = {{Count Data Models With Heterogeneous Peer Effects Under Rational Expectations}},
  author       = {Aristide Houndetoungan},
  journal      = {Journal of Applied Econometrics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/jae.70045},
}

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Count Data Models With Heterogeneous Peer Effects Under Rational Expectations

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.