Two-Step Estimation of Incomplete Information Social Interaction Models With Sample Selection
针对样本选择导致结果数据缺失的情况，提出两步序列非线性最小二乘估计法，用于估计不完全信息下的线性社会互动模型，并应用于青少年友谊互动对学业成绩影响的研究。
This article considers linear social interaction models under incomplete information that allow for missing outcome data due to sample selection. For model estimation, assuming that each individual forms his/her belief about the other members’ outcomes based on rational expectations, we propose a two-step series nonlinear least squares estimator. Both the consistency and asymptotic normality of the estimator are established. As an empirical illustration, we apply the proposed model and method to National Longitudinal Study of Adolescent Health (Add Health) data to examine the impacts of friendship interactions on adolescents’ academic achievements. We provide empirical evidence that the interaction effects are important determinants of grade point average and that controlling for sample selection bias has certain impacts on the estimation results. Supplementary materials for this article are available online.