Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Brodeur, Cook, and Heyes (2020) study hypothesis tests from economic articles and find evidence for p-hacking and publication bias, in particular for instrumental variable and difference-in-difference studies. When adjusting for rounding errors (introducing a novel method), statistical evidence for p-hacking from randomization tests and caliper tests at the 5 percent significance threshold vanishes for difference-in-difference studies but remains for instrumental variable studies. Results at the 1 percent and 10 percent significance thresholds remain largely similar. In addition, Brodeur, Cook, and Heyes derive latent distributions of z-statistics absent publication bias using two different approaches. We establish for each approach a result that challenges its applicability.