Abstract
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.
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