@article{14bea3f016524df491e957ef8398f782,
title = "The role of testing noise in the estimation of achievement-based peer effects",
abstract = "I demonstrate that in the value-added estimation of peer effects using lagged peer achievement, testing noise may generate another bias in addition to the well-known attenuation bias. Such a bias, which I refer to as the “reversion bias,” may arise when some of a student's current peers happen to be his/her former peers whose performances in the baseline test were subject to the same common testing noise as the student's own. I propose a solution to overcome this problem by exploiting only the variation in the new peers{\textquoteright} portion of the overall peer quality. Using real-world data, I illustrate the existence of this bias and demonstrate the proposed solution.",
keywords = "Mean reversion, Measurement error, Peer effects, Student achievement",
author = "Hongliang ZHANG",
note = "Funding Information: An earlier version of this paper was circulated under the title “Peer effects on student achievement: An instrumental variable approach using school transition data.” I thank Joshua Angrist, David Autor, Abhijit Banerjee, Jiahua Che, Weili Ding, Esther Duflo, Amy Finkelstein, Chih-Sheng Hsieh, Tao Jin, Rongzhu Ke, Lars Lefgren, Steven Lehrer, Weifeng Li, Karen Polenske, Christopher Taber, Yu Zhu, and seminar participants at Fudan University, Hong Kong University, Lingnan University, MIT, Peking University, Zhejiang University, Royal Economic Society Conference, and CUHK Symposium on the Economics of Education for their valuable comments and suggestions. I am also grateful to the co-editor and two anonymous referees for helpful comments and feedback, and to the UK Department of Education for access to the National Pupil Database. I acknowledge financial support from the Hong Kong Research Grant Council General Research Fund (No. 458610). All remaining errors are my own. ",
year = "2016",
month = oct,
day = "1",
doi = "10.1016/j.econedurev.2016.04.008",
language = "English",
volume = "54",
pages = "113--123",
journal = "Economics of Education Review",
issn = "0272-7757",
publisher = "Elsevier Ltd.",
}