Generalizing the group interaction model of Lee (2007), we identify and estimate the effects of student
level social spillovers on standardized test performance in New York City (NYC) elementary schools. We
leverage student demographic data to construct within-classroom social networks based on shared
student characteristics, such as a gender or ethnicity. Rather than aggregate shared characteristics into a
single network matrix, we specify additively separate network matrices for each shared characteristic
and estimate city-wide peer effects for each one. Conditional on being in the same classroom, we find
that the most important student peer effects are shared ethnicity, gender, and primary language spoken
at home. We show that altering classroom composition changes the impact of these networks.
Particularly, low ethnic diversity is correlated with low impact for shared ethnicity. We discuss
identification of the model and its implications for within- and between-group test performance gaps
along several demographic traits.