Count Data Models with Heterogeneous Peer Effects under Rational Expectations

43 Pages Posted: 19 Nov 2020 Last revised: 29 May 2024

Date Written: May 27, 2024

Abstract

This paper develops a micro-founded peer effect model for count responses using a game of incomplete information. The model incorporates heterogeneity in peer effects through agents' groups based on observed characteristics. Parameter identification is established using the identification condition of linear models, which relies on the presence of friends' friends who are not direct friends in the network. I show that this condition extends to a large class of nonlinear models. The model parameters are estimated using the nested pseudo-likelihood approach, controlling for network endogeneity. I present an empirical application on students' participation in extracurricular activities. I find that females are more responsive to their peers than males, whereas male peers do not influence male students. An easy-to-use R package—named CDatanet—is available for implementing the model.

Keywords: Discrete model, Social networks, Bayesian game, Rational expectations.

JEL Classification: C25, C31, C73, D84

Suggested Citation

Houndetoungan, Aristide, Count Data Models with Heterogeneous Peer Effects under Rational Expectations (May 27, 2024). Available at SSRN: https://ssrn.com/abstract=3721250 or http://dx.doi.org/10.2139/ssrn.3721250

Aristide Houndetoungan (Contact Author)

Cy Cergy Paris Université - THEMA ( email )

33 boulevard du Port
Cergy, 95011
France

HOME PAGE: http://ahoundetoungan.com

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
144
Abstract Views
1,395
Rank
392,588
PlumX Metrics