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Identifying Social Interactions Through Conditional Variance Restrictions
Bryan S. Graham
Abstract
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.
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