Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The nonparametric identification of the local average treatment effect (LATE) hinges on the satisfaction of three instrumental variable assumptions: (1) unconfounded assignment of the instrument, (2) no average direct effect of the instrument on the outcome within compliance types (exclusion restriction), and (3) weak monotonicity of the treatment in the instrument. While (1) often appears plausible in experiments when using randomization as instrument for actual participation, (2) and (3) may be controversial. For this reason, this paper proposes easily implementable sensitivity checks to assess the robustness of the LATE to deviations from either the exclusion restriction or monotonicity. An empirical illustration based on female labor supply data is also provided.