Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Identification of peer effects is complicated by the fact that the individuals under study may select their peers. Random assignment to peer groups has proven useful to sidestep such a concern. In the absence of a formal randomization mechanism, it needs to be argued that assignment is “as good as” random. This paper introduces a simple yet powerful test to do so. We provide theoretical results for this test. As a by‐product, we equally obtain such results for an approach popularized by Guryan et al. (2009). These results help to explain why this approach suffers from low power, as has been observed elsewhere.