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Inference on Peer Effects with Missing Peer Data: Evidence from Project STAR

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Author Info
Aaron Sojourner ()

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Abstract

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 a new way, given random assignment of individuals to classes, to identify peer effects without other missing-data assumptions. Estimates suggest moderate, positive effects of mean peer lagged achievement. Allowing heterogeneous effects, evidence suggests lower-achieving students benefit more than higher-achieving students do from increases in peer mean. Further, the bias of a widely used but poorly understood peer-effects estimator is characterized.

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Paper provided by Industrial Relations Center, University of Minnesota (Twin Cities Campus) in its series Working Papers with number 0109.

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Handle: RePEc:hrr:papers:0109

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Find related papers by JEL classification:
C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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This page was last updated on 2009-12-12.

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