Cited by 333Advanced Causal Inference TechniquesMeta-analysis and systematic reviewsscientometrics and bibliometrics research

Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics

Brodeur, Abel, Cook, Nikolai, Heyes, Anthony·2020·American Economic Review

Abstract

The credibility revolution in economics has promoted causal identification using randomized control trials (RCT), difference-in-differences (DID), instrumental variables (IV) and regression discontinuity design (RDD). Applying multiple approaches to over 21,000 hypothesis tests published in 25 leading economics journals, we find that the extent of p-hacking and publication bias varies greatly by method. IV (and to a lesser extent DID) are particularly problematic. We find no evidence that (i) papers published in the Top 5 journals are different to others; (ii) the journal “revise and resubmit” process mitigates the problem; (iii) things are improving through time. (JEL A14, C12, C52)

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Crossref · 10.1257/aer.20190687

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Authors
Brodeur, A., Cook, N., & Heyes, A.
Affiliations
University of Ottawa (CA)
Venue
American Economic Review
Published
2020-11-01
Volume
110
Issue
11
Pages
3634-3660
ISSN
0002-8282 (ISSN-L)
OpenAlex
W3047016911
Cited by
333
References
41
Citations by year
2026: 44 · 2025: 50 · 2024: 91 · 2023: 49 · 2022: 47 · 2021: 41 · 2020: 7 · 2019: 2 · 2018: 1 · 2014: 1
FWCI
25.39
Type
journal article
Language
en
Open access
closed
Locations
  • American Economic Review (publishedVersion)
  • Open Research Exeter (University of Exeter) (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Figshare (submittedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
Keywords
p-hacking, publication bias, credibility revolution, causal inference, instrumental variables, difference-in-differences, regression discontinuity design, randomized controlled trials, hypothesis testing, economics journals

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