Published March 19, 2024 | Version v1
Journal article Open

Randomization Tests for Peer Effects in Group Formation Experiments

  • 1. Citadel Securities
  • 2. University of California, Berkeley
  • 3. University of Chicago

Description

Measuring the effect of peers on individuals' outcomes is a challenging problem, in part because individuals often select peers who are similar in both observable and unobservable ways. Group formation experiments avoid this problem by randomly assigning individuals to groups and observing their responses; for example, do first-year students have better grades when they are randomly assigned roommates who have stronger academic backgrounds? In this paper, we propose randomization-based permutation tests for group formation experiments, extending classical Fisher Randomization Tests to this setting. The proposed tests are justified by the randomization itself, require relatively few assumptions, and are exact in finite samples. This approach can also complement existing strategies, such as linear-in-means models, by using a regression coefficient as the test statistic. We apply the proposed tests to two recent group formation experiments.

Data availability

The replication package for this paper is available at https://doi.org/10.5281/zenodo.8336416. The authors were granted an exemption to publish their data because either access to the data is restricted or the authors do not have the right to republish them. Therefore, the replication package only includes the codes but not the data. However, the authors provided the Journal with (or assisted the Journal to obtain) temporary access to the data. The Journal checked the restricted data and the provided codes for their ability to reproduce the results in the paper and approved online appendices.

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Additional details

Identifiers

DOI
10.3982/ECTA20134
Other
oai:uchicago.tind.io:11381

Funding

U.S. National Science Foundation
Collaborative Research: Theoretical and Methodological Frameworks for Causal Inference of Peer Effects
U.S. National Science Foundation
CAREER: The Design-Based Perspective of Causal Inference in Complex Experiments
National Academy of Education/Spencer Foundation
postdoctoral fellowship
University of Chicago
John E. Jeuck Fellowship

UChicago Information

Division(s)
Booth School of Business
Department(s)
Econometrics and Statistics