Aaron Sojourner (University of Minnesota), “Identification of Peer Effects with Missing Peer Data: Evidence from Project STAR”, Journal of Applied Econometrics Seminar, Toulouse : TSE, October 19, 2010, 15:30–17:00, room MF 323.
This paper studies peer effects on student achievement among first graders randomly assigned to classrooms in Tennessee's Project STAR. The analysis uses previously unexploited pre-assignment achievement measures available for sixty percent of students. Data are not missing at random, making identification challenging. The paper develops new ways, given random assignment of individuals to classes, to identify peer effects without imposing other missing-data assumptions. Estimates suggest positive effects of mean peer lagged achievement on average. Allowing heterogeneous effects, evidence suggests lowerachieving students benefit more than higher-achieving students do from increases in peer mean. Further, the bias in a widely used, poorly understood peer-effects estimator is analyzed, implying that caution is warranted in interpreting many peer-effect estimates extant in the literature.
- C2: Single Equation Models • Single Variables
- I21: Analysis of Education
- J13: Fertility • Family Planning • Child Care • Children • Youth