Count Data Models With Heterogeneous Peer Effects Under Rational Expectations
开发了一个在理性预期下处理计数响应数据的同伴效应模型，允许同伴效应因群体特征而异，并利用朋友的朋友作为识别条件，通过嵌套伪似然法估计参数。实证发现女生对同伴的反应比男生更敏感。
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.