IDEAS home Printed from https://ideas.repec.org/p/zbw/glodps/1147.html
   My bibliography  Save this paper

Do Pre-Registration and Pre-analysis Plans Reduce p-Hacking and Publication Bias?

Author

Listed:
  • Brodeur, Abel
  • Cook, Nikolai M.
  • Hartley, Jonathan S.
  • Heyes, Anthony

Abstract

Randomized controlled trials (RCTs) are increasingly prominent in economics, with pre-registration and pre-analysis plans (PAPs) promoted as important in ensuring the credibility of findings. We investigate whether these tools reduce the extent of p-hacking and publication bias by collecting and studying the universe of test statistics, 15,992 in total, from RCTs published in 15 leading economics journals from 2018 through 2021. In our primary analysis, we find no meaningful difference in the distribution of test statistics from pre-registered studies, compared to their non-pre-registered counterparts. However, pre-registered studies that have a complete PAP are significantly less p-hacked. These results point to the importance of PAPs, rather than pre-registration in itself, in ensuring credibility.

Suggested Citation

  • Brodeur, Abel & Cook, Nikolai M. & Hartley, Jonathan S. & Heyes, Anthony, 2022. "Do Pre-Registration and Pre-analysis Plans Reduce p-Hacking and Publication Bias?," GLO Discussion Paper Series 1147, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:1147
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/262738/1/GLO-DP-1147.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
    2. Matias D. Cattaneo & Michael Jansson & Xinwei Ma, 2020. "Simple Local Polynomial Density Estimators," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1449-1455, July.
    3. 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.
    4. Luigi Butera & Philip Grossman & Daniel Houser & John List & Marie-Claire Villeval, 2020. "A New Mechanism to Alleviate the Crises of Confidence in Science - With an Application to the Public Goods Game," Artefactual Field Experiments 00684, The Field Experiments Website.
    5. Benjamin A. Olken, 2015. "Promises and Perils of Pre-analysis Plans," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 61-80, Summer.
    6. 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.
    7. Gerber, Alan & Malhotra, Neil, 2008. "Do Statistical Reporting Standards Affect What Is Published? Publication Bias in Two Leading Political Science Journals," Quarterly Journal of Political Science, now publishers, vol. 3(3), pages 313-326, October.
    8. Martin Ravallion, 2018. "Should the Randomistas (Continue to) Rule?," Working Papers 492, Center for Global Development, revised 17 Jan 2019.
    9. Isaiah Andrews & Maximilian Kasy, 2019. "Identification of and Correction for Publication Bias," American Economic Review, American Economic Association, vol. 109(8), pages 2766-2794, August.
    10. Cristina Blanco-Perez & Abel Brodeur, 2020. "Publication Bias and Editorial Statement on Negative Findings," The Economic Journal, Royal Economic Society, vol. 130(629), pages 1226-1247.
    11. Burlig, Fiona, 2018. "Improving transparency in observational social science research: A pre-analysis plan approach," Economics Letters, Elsevier, vol. 168(C), pages 56-60.
    12. Eva Vivalt, 2019. "Specification Searching and Significance Inflation Across Time, Methods and Disciplines," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 797-816, August.
    13. Tomáš Havránek, 2015. "Measuring Intertemporal Substitution: The Importance Of Method Choices And Selective Reporting," Journal of the European Economic Association, European Economic Association, vol. 13(6), pages 1180-1204, December.
    14. Tomas Havranek & Anna Sokolova, 2020. "Do Consumers Really Follow a Rule of Thumb? Three Thousand Estimates from 144 Studies Say 'Probably Not'," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 35, pages 97-122, January.
    15. Lucas C. Coffman & Muriel Niederle, 2015. "Pre-analysis Plans Have Limited Upside, Especially Where Replications Are Feasible," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 81-98, Summer.
    16. Edward Miguel, 2021. "Evidence on Research Transparency in Economics," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 193-214, Summer.
    17. Katherine Casey & Rachel Glennerster & Edward Miguel, 2012. "Reshaping Institutions: Evidence on Aid Impacts Using a Preanalysis Plan," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(4), pages 1755-1812.
    18. George K. Ofosu & Daniel N. Posner, 2020. "Do Pre-analysis Plans Hamper Publication?," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 70-74, May.
    19. Garret Christensen & Allan Dafoe & Edward Miguel & Don A Moore & Andrew K Rose, 2019. "A study of the impact of data sharing on article citations using journal policies as a natural experiment," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-13, December.
    20. Jens Ludwig & Sendhil Mullainathan & Jann Spiess, 2019. "Augmenting Pre-Analysis Plans with Machine Learning," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 71-76, May.
    21. Beare, Brendan K. & Moon, Jong-Myun, 2015. "Nonparametric Tests Of Density Ratio Ordering," Econometric Theory, Cambridge University Press, vol. 31(3), pages 471-492, June.
    22. Luigi Butera & Philip J Grossman & Daniel Houser & John A List & Marie Claire Villeval, 2020. "A New Mechanism to Alleviate the Crises of Confidence in Science With An Application to the Public Goods GameA Review," Working Papers halshs-02512932, HAL.
    23. Chris Doucouliagos & T.D. Stanley, 2013. "Are All Economic Facts Greatly Exaggerated? Theory Competition And Selectivity," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 316-339, April.
    24. Drazen, Allan & Dreber, Anna & Ozbay, Erkut Y. & Snowberg, Erik, 2021. "Journal-based replication of experiments: An application to “Being Chosen to Lead”," Journal of Public Economics, Elsevier, vol. 202(C).
    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. Abel Brodeur & Scott Carrell & David Figlio & Lester Lusher, 2023. "Unpacking P-hacking and Publication Bias," American Economic Review, American Economic Association, vol. 113(11), pages 2974-3002, November.
    2. Thibaut Arpinon & Romain Espinosa, 2023. "A practical guide to Registered Reports for economists," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 9(1), pages 90-122, June.
    3. Danielle V. Handel & Eric A. Hanushek, 2024. "Contexts of Convenience: Generalizing from Published Evaluations of School Finance Policies," Evaluation Review, , vol. 48(3), pages 461-494, June.
    4. Thibaut Arpinon & Romain Espinosa, 2023. "A Practical Guide to Registered Reports for Economists," Post-Print halshs-03897719, HAL.
    5. Sam Sims & Jake Anders & Matthew Inglis & Hugues Lortie-Forgues & Ben Styles & Ben Weidmann, 2023. "Experimental education research: rethinking why, how and when to use random assignment," CEPEO Working Paper Series 23-07, UCL Centre for Education Policy and Equalising Opportunities, revised Aug 2023.

    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. Abel Brodeur & Nikolai M. Cook & Jonathan S. Hartley & Anthony Heyes, 2024. "Do Preregistration and Preanalysis Plans Reduce p-Hacking and Publication Bias? Evidence from 15,992 Test Statistics and Suggestions for Improvement," Journal of Political Economy Microeconomics, University of Chicago Press, vol. 2(3), pages 527-561.
    2. Abel Brodeur & Nikolai Cook & Carina Neisser, 2024. "p-Hacking, Data type and Data-Sharing Policy," The Economic Journal, Royal Economic Society, vol. 134(659), pages 985-1018.
    3. 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.
    4. 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.
    5. Furukawa, Chishio, 2019. "Publication Bias under Aggregation Frictions: Theory, Evidence, and a New Correction Method," EconStor Preprints 194798, ZBW - Leibniz Information Centre for Economics.
    6. Graham Elliott & Nikolay Kudrin & Kaspar Wüthrich, 2022. "Detecting p‐Hacking," Econometrica, Econometric Society, vol. 90(2), pages 887-906, March.
    7. Graham Elliott & Nikolay Kudrin & Kaspar Wuthrich, 2022. "The Power of Tests for Detecting $p$-Hacking," Papers 2205.07950, arXiv.org, revised Apr 2024.
    8. Anna Dreber & Magnus Johannesson & Yifan Yang, 2024. "Selective reporting of placebo tests in top economics journals," Economic Inquiry, Western Economic Association International, vol. 62(3), pages 921-932, July.
    9. Cristina Blanco-Perez & Abel Brodeur, 2020. "Publication Bias and Editorial Statement on Negative Findings," The Economic Journal, Royal Economic Society, vol. 130(629), pages 1226-1247.
    10. Edward Miguel, 2021. "Evidence on Research Transparency in Economics," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 193-214, Summer.
    11. Tomas Havranek & Zuzana Irsova & Lubica Laslopova & Olesia Zeynalova, 2020. "Skilled and Unskilled Labor Are Less Substitutable than Commonly Thought," Working Papers IES 2020/29, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2020.
    12. 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).
    13. Abel Brodeur & Scott Carrell & David Figlio & Lester Lusher, 2023. "Unpacking P-hacking and Publication Bias," American Economic Review, American Economic Association, vol. 113(11), pages 2974-3002, November.
    14. Brodeur, Abel & Cook, Nikolai & Heyes, Anthony, 2018. "Methods Matter: P-Hacking and Causal Inference in Economics," IZA Discussion Papers 11796, Institute of Labor Economics (IZA).
    15. Ali Elminejad & Tomas Havranek & Roman Horvath & Zuzana Irsova, 2023. "Intertemporal Substitution in Labor Supply: A Meta-Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 1095-1113, December.
    16. Sarah A. Janzen & Jeffrey D. Michler, 2021. "Ulysses' pact or Ulysses' raft: Using pre‐analysis plans in experimental and nonexperimental research," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1286-1304, December.
    17. Abel Brodeur, Nikolai M. Cook, Anthony Heyes, 2022. "We Need to Talk about Mechanical Turk: What 22,989 Hypothesis Tests Tell Us about Publication Bias and p-Hacking in Online Experiments," LCERPA Working Papers am0133, Laurier Centre for Economic Research and Policy Analysis.
    18. Doucouliagos, Hristos & Hinz, Thomas & Zigova, Katarina, 2022. "Bias and careers: Evidence from the aid effectiveness literature," European Journal of Political Economy, Elsevier, vol. 71(C).
    19. Roman Horvath & Ali Elminejad & Tomas Havranek, 2020. "Publication and Identification Biases in Measuring the Intertemporal Substitution of Labor Supply," Working Papers IES 2020/32, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2020.
    20. Cazachevici, Alina & Havranek, Tomas & Horvath, Roman, 2020. "Remittances and economic growth: A meta-analysis," World Development, Elsevier, vol. 134(C).

    More about this item

    Keywords

    Pre-analysis plan; Pre-registration; p-Hacking; Publication bias; Research credibility;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:glodps:1147. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/glabode.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.