Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Regression-discontinuity (RD) designs estimate treatment effects only around a cutoff. This paper shows what can be learned about average treatment effects for the treated (ATT), untreated (ATUT), and population (ATE) if the cutoff was chosen to maximize the net gain from treatment. Without capacity constraints, the RD estimate bounds the ATT from below and the ATUT from above, implying bounds for the ATE, and optimality of the cutoff rules out constant treatment effects. Bounds are typically looser if the capacity constraint binds. Testable implications of cutoff optimality are derived. The results are demonstrated using previous RD studies.