Econometrica Vol. 90 No. 2 2022
Detecting p‐Hacking
Abstract
We theoretically analyze the problem of testing for p ‐hacking based on distributions of p ‐values across multiple studies. We provide general results for when such distributions have testable restrictions (are non‐increasing) under the null of no p ‐hacking. We find novel additional testable restrictions for p ‐values based on t ‐tests. Specifically, the shape of the power functions results in both complete monotonicity as well as bounds on the distribution of p ‐values. These testable restrictions result in more powerful tests for the null hypothesis of no p ‐hacking. When there is also publication bias, our tests are joint tests for p ‐hacking and publication bias. A reanalysis of two prominent data sets shows the usefulness of our new tests.
- DOI
- 10.3982/ecta18583
- Volume
- 90
- Issue
- 2
- Pages
- 887-906
- Language
- en
- Sources
- bibtex:phds-export.bib openalex crossref