TY  - JOUR
PY  - 2023//
TI  - Unpacking p-hacking and publication bias
JO  - American economic review
A1  - Brodeur, Abel
A1  - Carrell, Scott
A1  - Figlio, David
A1  - Lusher, Lester
SP  - 2974
EP  - 3002
VL  - 113
IS  - 11
N2  - We use unique data from journal submissions to identify and unpack publication bias and p-hacking. We find initial submissions display significant bunching, suggesting the distribution among published statistics cannot be fully attributed to a publication bias in peer review. Desk-rejected 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.<p />  <p>Language: en</p>
LA  - en
SN  - 0002-8282
UR  - http://dx.doi.org/10.1257/aer.20210795
ID  - ref1
ER  -