Identifying Social Interactions Through Conditional Variance Restrictions
提出一种利用条件方差限制来识别社会互动的新方法，能一致估计线性均值形式的社会乘数，并用于检验无社会互动的原假设。基于田纳西州STAR实验数据的应用表明，同伴质量差异是幼儿园学生学业成绩个体差异的重要来源。
This paper proposes a new method for identifying social interactions using conditional variance restrictions. The method provides a consistent estimate of the social multiplier when social interactions take the "linear-in-means" form (Manski (1993)). When social interactions are not of the linear-in-means form, the estimator, under certain conditions, continues to form the basis of a consistent test of the no social interactions null with correct large sample size. The methods are illustrated using data from the Tennessee class size reduction experiment Project STAR. The application suggests that differences in peer group quality were an important source of individual-level variation in the academic achievement of Project STAR kindergarten students. Copyright Copyright 2008 by The Econometric Society.