Arbeitspapier

Unpacking P-Hacking and Publication Bias

We use unique data from journal submissions to identify and unpack publication bias and p-hacking. 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. 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.

Language
Englisch

Bibliographic citation
Series: I4R Discussion Paper Series ; No. 52

Classification
Wirtschaft
Role of Economics; Role of Economists; Market for Economists
Estimation: General
Econometric and Statistical Methods: Special Topics: General
Subject
publication bias
p-hacking
selective reporting

Event
Geistige Schöpfung
(who)
Brodeur, Abel
Carrell, Scott
Figlio, David
Lusher, Lester
Event
Veröffentlichung
(who)
Institute for Replication (I4R)
(where)
s.l.
(when)
2023

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Arbeitspapier

Associated

  • Brodeur, Abel
  • Carrell, Scott
  • Figlio, David
  • Lusher, Lester
  • Institute for Replication (I4R)

Time of origin

  • 2023

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