Unpacking P-Hacking and Publication Bias
Abel Brodeur, Scott Carrell, David Figlio, Lester R. Lusher · National Bureau of Economic Research · 2023
We use unique data from journal submissions to identify and unpack publication bias and phacking.We find that initial submissions display significant bunching, suggesting the distribution among published statistics cannot be fully attributed to a publication bias in peer review.Deskrejected manuscripts display greater heaping than those sent for review i.e. marginally significant results are more likely to be desk rejected.Reviewer recommendations, in contrast, are positively associated with statistical significance.Overall, the peer review process has little effect on the distribution of test statistics.Lastly, we track rejected papers and present evidence that the prevalence of publication biases is perhaps not as prominent as feared.