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Pá 31.01.2014

Santiago Pereda Fernández (JOB TALK): “Social Spillovers in the Classroom: Identification, Estimation and Policy Analysis”

Santiago Pereda Fernández

University of California, Berkeley, USA

Author: Santiago Pereda-Fernández

Abstract: In this paper I present a new method to identify and estimate the strength of social spillovers in the classroom and the distribution of teacher and student effects. The identification depends on the assumptions of double randomization of teacher and students to classrooms and the linear in means equation of test scores. The linear independent factor representation of test scores allows one to obtain more efficient estimates of the social multiplier by combining all the joint moments of different orders. I also present a theoretical model of social interactions in the classroom that yields the linear in means equation for test scores. In this model, the teacher and students play a game in which they choose how much effort to exert. The method I provide allows the estimation of more features of the distribution of teacher and student effects than the mean and variance. Moreover, it becomes straightforward to accomodate class size heteroskedastic teacher and student effects. For the estimation, I use a minimum distance procedure that combines the information coming from different moments. Using the Tennessee Project STAR dataset, I find sizeable spillovers in the classroom. Moreover, the distributions of teacher and student abilities seem to depart from the usual normality assumption, and the student distribution exhibits a high degree of heteroskedasticity in class size. Based on these estimates, I perform several counterfactual social planning experiments, comparing who are the losers and winners under different assignment rules. Assignment of good teachers to large classrooms increases the average test scores, with students in the left tail of the distribution benefiting more than the rest. Assignment of good students to small classrooms increases the test scores of students in the right tail of the distribution, while decreasing test scores of students in the left tail of the distribution, with an overall increase in mean test scores. Mixing good and bad students together results in a small effect on mean test scores, but reduces inequality.

Full Text:  “Social Spillovers in the Classroom: Identification, Estimation and Policy Analysis”