Quantile Effects in Discrete Choice with Social Interactions
提出一种方法研究社会互动下离散选择的分位数效应，基于分位数偏好行为模型，用嵌套伪得分法估计同伴效应，并通过学生运动决策数据验证。
Abstract This paper provides a method to study quantile effects in discrete choice with social interactions. The method is based on a behavioral social interactions model from quantile preference in decision making and demonstrates peer effects on different quantiles of discrete outcomes. The peer effects parameters are estimated by a nested pseudo score (NPS) approach, which is developed to tackle the computational burden pertaining to the social interactions model. Consistency and asymptotic normality are established for the proposed NPS estimator. We illustrate the finite sample performance of the model and the estimator by Monte Carlo experiments and an application of peer effects among students on exercise decisions, using the National Longitudinal Study of Adolescent Health dataset.