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Exploiting Regression-Discontinuity Design to Estimate Peer Effects in College – The Case of Class Attendance

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Listed:
  • Qihui Chen

    (China Agricultural University)

  • Tade Okediji

    (University of Minnesota)

  • Tian Guoqiang

    (China Agricultural University)

Abstract

We exploit a regression-discontinuity design to estimate peer effects on college students' attendance, using data from a classroom experiment, which required students who scored below a cut-off on the first midterm exam to attend subsequent classes. Since within a small interval around the cut-off, which side of the cut-off a student falls is randomly determined, so is the proportion of a student's classmates falling on one side of the cut-off in the same interval. Using this proportion to instrument peer attendance, we find that a one-point (out of ten) increase in classmates' average attendance score raises a student's attendance score by 0.7 points.

Suggested Citation

  • Qihui Chen & Tade Okediji & Tian Guoqiang, 2015. "Exploiting Regression-Discontinuity Design to Estimate Peer Effects in College – The Case of Class Attendance," Economics Bulletin, AccessEcon, vol. 35(3), pages 1563-1571.
    • Handle: RePEc:ebl:ecbull:eb-14-00808
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    References listed on IDEAS

    as
    1. Qihui Chen & Guoqiang Tian & Tade O. Okediji, 2014. "Quasi-Experimental Evidence of Peer Effects in First-Year Economics Courses at a Chinese University," The Journal of Economic Education, Taylor & Francis Journals, vol. 45(4), pages 304-319, December.
    2. Stinebrickner, Ralph & Stinebrickner, Todd R., 2006. "What can be learned about peer effects using college roommates? Evidence from new survey data and students from disadvantaged backgrounds," Journal of Public Economics, Elsevier, vol. 90(8-9), pages 1435-1454, September.
    3. Qihui Chen & Tade O. Okediji, 2014. "Incentive Matters!-The Benefit of Reminding Students About Their Academic Standing in Introductory Economics Courses," The Journal of Economic Education, Taylor & Francis Journals, vol. 45(1), pages 11-24, March.
    4. David J. Zimmerman, 2003. "Peer Effects in Academic Outcomes: Evidence from a Natural Experiment," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 9-23, February.
    5. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    6. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    7. Bruce Sacerdote, 2001. "Peer Effects with Random Assignment: Results for Dartmouth Roommates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(2), pages 681-704.
    8. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
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    Cited by:

    1. de Souza, Laeticia R. & de Xavier Pinto, Cristine Campos & Queiroz, Bernardo L & de Oliveira e Silva, Dimitri, 2021. "Peer effects in college: how peers' performance can influence students' academic outcomes," SocArXiv 7n6ks, Center for Open Science.

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    More about this item

    Keywords

    Peer Effects; Regression-discontinuity;

    JEL classification:

    • A2 - General Economics and Teaching - - Economic Education and Teaching of Economics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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