The DOI matches its Crossref record.
Understanding Peer Effects: On the Nature, Estimation, and Channels of Peer Effects
Open accessAbstract
This paper estimates peer effects in a university context where students are randomly assigned to sections. While students benefit from better peers on average, low-achieving students are harmed by high-achieving peers. Analyzing students’ course evaluations suggests that peer effects are driven by improved group interaction rather than adjustments in teachers’ behavior or students’ effort. Building on Angrist’s research, we further show that classical measurement error in a setting where group assignment is systematic can lead to a substantial overestimation of peer effects. However, when group assignment is random—like in our setting—peer effect estimates are biased toward zero.
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Citations
Cited by
Gender Bias in Teaching Evaluations
Mengel, F., Sauermann, J., & Zölitz, U. (2019) · Journal of the European Economic Association · doi:10.1093/jeea/jvx057 · Cited by 401
Self-citationLaidley, T., Vinneau, J., & Boardman, J. (2019) · Sociological Science · doi:10.15195/v6.a22 · Cited by 11
Metadata
- Authors
- Feld, J., & Zölitz, U.
- Venue
- Journal of Labor Economics
- Publisher
- University of Chicago Press
- Published
- 2017-04
- Volume
- 35
- Issue
- 2
- Pages
- 387-428
- ISSN
- 0734-306X (ISSN-L)
- 1537-5307
- OpenAlex
- W2152729542
- Cited by
- 295
- References
- 0
- FWCI
- 88.47
- Type
- journal article
- Language
- en
- Open access
- green
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- Feld, J., & Zölitz, U. (2017). Understanding Peer Effects: On the Nature, Estimation, and Channels of Peer Effects. Journal of Labor Economics. https://doi.org/10.1086/689472
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
