IDEAS home Printed from https://ideas.repec.org/a/aea/aecrev/v112y2022i9p3137-39.html
   My bibliography  Save this article

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

Author

Listed:
  • Abel Brodeur
  • Nikolai Cook
  • Anthony Heyes

Abstract

In Brodeur, Cook, and Heyes (2020) we present evidence that instrumental variable (and to a lesser extent difference-in-difference) articles are more p-hacked than randomized controlled trial and regression discontinuity design articles. We also find no evidence that (i) articles published in the top five journals are different; (ii) the "revise and resubmit" process mitigates the problem; (iii) things are improving through time. Kranz and Pütz (2022) apply a novel adjustment to address rounding errors. They successfully replicate our results with the exception of our shakiest finding: after adjusting for rounding errors, bunching of test statistics for difference-in-difference articles is now smaller around the 5 percent level (and coincidentally larger at the 10 percent level).

Suggested Citation

  • Abel Brodeur & Nikolai Cook & Anthony Heyes, 2022. "Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics: Reply," American Economic Review, American Economic Association, vol. 112(9), pages 3137-3139, September.
  • Handle: RePEc:aea:aecrev:v:112:y:2022:i:9:p:3137-39
    DOI: 10.1257/aer.20220277
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/aer.20220277
    Download Restriction: no

    File URL: https://doi.org/10.3886/E165621V1
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/aer.20220277.appx
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/aer.20220277.ds
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.

    File URL: https://libkey.io/10.1257/aer.20220277?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
    2. Abel Brodeur & Nikolai Cook & Anthony Heyes, 2020. "Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics," American Economic Review, American Economic Association, vol. 110(11), pages 3634-3660, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ankel-Peters, Jörg & Fiala, Nathan & Neubauer, Florian, 2023. "Do economists replicate?," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 219-232.
    2. Danielle V. Handel & Eric A. Hanushek, 2023. "Contexts of Convenience: Generalizing from Published Evaluations of School Finance Policies," NBER Working Papers 31653, National Bureau of Economic Research, Inc.
    3. Ankel-Peters, Jörg & Schmidt, Christoph M., 2023. "Rural electrification, the credibility revolution, and the limits of evidence-based policy," Ruhr Economic Papers 1051, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stefano DellaVigna & Elizabeth Linos, 2022. "RCTs to Scale: Comprehensive Evidence From Two Nudge Units," Econometrica, Econometric Society, vol. 90(1), pages 81-116, January.
    2. Bruns, Stephan & Herwartz, Helmut & Ioannidis, John P.A. & Islam, Chris-Gabriel & Raters, Fabian H. C., 2023. "Statistical reporting errors in economics," MetaArXiv mbx62, Center for Open Science.
    3. Christoph Huber & Christian König-Kersting, 2022. "Experimenting with Financial Professionals," Working Papers 2022-07, Faculty of Economics and Statistics, Universität Innsbruck.
    4. Brodeur, Abel & Cook, Nikolai & Heyes, Anthony, 2022. "We Need to Talk about Mechanical Turk: What 22,989 Hypothesis Tests Tell Us about Publication Bias and p-Hacking in Online Experiments," IZA Discussion Papers 15478, Institute of Labor Economics (IZA).
    5. Uwe Hassler & Marc‐Oliver Pohle, 2022. "Unlucky Number 13? Manipulating Evidence Subject to Snooping," International Statistical Review, International Statistical Institute, vol. 90(2), pages 397-410, August.
    6. Jasper Brinkerink, 2023. "When Shooting for the Stars Becomes Aiming for Asterisks: P-Hacking in Family Business Research," Entrepreneurship Theory and Practice, , vol. 47(2), pages 304-343, March.
    7. Gechert, Sebastian & Mey, Bianka & Opatrny, Matej & Havranek, Tomas & Stanley, T. D. & Bom, Pedro R. D. & Doucouliagos, Hristos & Heimberger, Philipp & Irsova, Zuzana & Rachinger, Heiko J., 2023. "Conventional Wisdom, Meta-Analysis, and Research Revision in Economics," EconStor Preprints 280745, ZBW - Leibniz Information Centre for Economics.
    8. Dreber, Anna & Johannesson, Magnus, 2023. "A framework for evaluating reproducibility and replicability in economics," Ruhr Economic Papers 1055, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    9. Graham Elliott & Nikolay Kudrin & Kaspar Wüthrich, 2022. "Detecting p‐Hacking," Econometrica, Econometric Society, vol. 90(2), pages 887-906, March.
    10. Brodeur, Abel & Cook, Nikolai & Heyes, Anthony, 2022. "We Need to Talk about Mechanical Turk: What 22,989 Hypothesis Tests Tell us about p-Hacking and Publication Bias in Online Experiments," GLO Discussion Paper Series 1157, Global Labor Organization (GLO).
    11. Brodeur, Abel & Esterling, Kevin & Ankel-Peters, Jörg & Bueno, Natália S. & Desposato, Scott & Dreber, Anna & Genovese, Federica & Green, Donald P. & Hepplewhite, Matthew & Hoces de la Guardia, Fernan, 2024. "Promoting Reproducibility and Replicability in Political Science," I4R Discussion Paper Series 100, The Institute for Replication (I4R).
    12. Adam Gorajek & Benjamin A. Malin, 2021. "Comment on "Star Wars: The Empirics Strike Back"," Staff Report 629, Federal Reserve Bank of Minneapolis.
    13. Roggenkamp, Hauke C., 2024. "Revisiting ‘Growth and Inequality in Public Good Provision’—Reproducing and Generalizing Through Inconvenient Online Experimentation," OSF Preprints 6rn97, Center for Open Science.
    14. Felix Chopra & Ingar Haaland & Christopher Roth & Andreas Stegmann, 2023. "The Null Result Penalty," The Economic Journal, Royal Economic Society, vol. 134(657), pages 193-219.
    15. Graham Elliott & Nikolay Kudrin & Kaspar Wuthrich, 2022. "The Power of Tests for Detecting $p$-Hacking," Papers 2205.07950, arXiv.org, revised Jun 2023.
    16. Picchio, Matteo & Ubaldi, Michele, 2022. "Unemployment and Health: A Meta-Analysis," GLO Discussion Paper Series 1128, Global Labor Organization (GLO).
    17. Brodeur, Abel & Cook, Nikolai & Neisser, Carina, 2022. "P-Hacking, Data Type and Data-Sharing Policy," IZA Discussion Papers 15586, Institute of Labor Economics (IZA).
    18. Kaiser, Tim & Lusardi, Annamaria & Menkhoff, Lukas & Urban, Carly, 2022. "Financial education affects financial knowledge and downstream behaviors," Journal of Financial Economics, Elsevier, vol. 145(2), pages 255-272.
    19. Dominika Ehrenbergerova & Josef Bajzik & Tomas Havranek, 2023. "When Does Monetary Policy Sway House Prices? A Meta-Analysis," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 538-573, June.
    20. Brodeur, Abel & Cook, Nikolai & Hartley, Jonathan & Heyes, Anthony, 2022. "Do Pre-Registration and Pre-analysis Plans Reduce p-Hacking and Publication Bias?," MetaArXiv uxf39, Center for Open Science.

    More about this item

    JEL classification:

    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:aecrev:v:112:y:2022:i:9:p:3137-39. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.