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P-Hacking, Data Type and Data-Sharing Policy

Author

Listed:
  • Abel Brodeur

    (University of Ottawa and IZA)

  • Nikolai Cook

    (Wilfrid Laurier University)

  • Carina Neisser

    (University of Cologne and IZA)

Abstract
In this paper, we examine the relationship between p-hacking and data sharing policies for published articles. We collect 38,876 test statistics from 1,106 articles published in leading economic journals between 2002–2020. While a data-sharing policy increases the provision of research data to the community, we find a well-estimated null effect that requiring authors to share their data at the time of publication does not alter the presence of p-hacking. Similarly, articles that use hard-to-access administrative data or third-party surveys, as compared to those that use easier-to-access (e.g., own-collected) data are not different in their p-hacking extent. Voluntary provision of data by authors on their homepages offers no evidence of reduced p-hacking.

Suggested Citation

  • Abel Brodeur & Nikolai Cook & Carina Neisser, 2022. "P-Hacking, Data Type and Data-Sharing Policy," ECONtribute Discussion Papers Series 200, University of Bonn and University of Cologne, Germany.
    • Handle: RePEc:ajk:ajkdps:200
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    References listed on IDEAS

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    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. B.D. McCullough & Kerry Anne McGeary & Teresa D. Harrison, 2008. "Do economics journal archives promote replicable research?," Canadian Journal of Economics, Canadian Economics Association, vol. 41(4), pages 1406-1420, November.
    3. 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.
    4. Arie Kapteyn & Jelmer Y. Ypma, 2007. "Measurement Error and Misclassification: A Comparison of Survey and Administrative Data," Journal of Labor Economics, University of Chicago Press, vol. 25(3), pages 513-551.
    5. Alberto Abadie, 2020. "Statistical Nonsignificance in Empirical Economics," American Economic Review: Insights, American Economic Association, vol. 2(2), pages 193-208, June.
    6. John P. A. Ioannidis & T. D. Stanley & Hristos Doucouliagos, 2017. "The Power of Bias in Economics Research," Economic Journal, Royal Economic Society, vol. 127(605), pages 236-265, October.
    7. 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.
    8. Jérôme Adda & Christian Decker & Marco Ottaviani, 2020. "P-hacking in clinical trials and how incentives shape the distribution of results across phases," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(24), pages 13386-13392, June.
    9. David Card & Stefano DellaVigna & Patricia Funk & Nagore Iriberri, 2020. "Are Referees and Editors in Economics Gender Neutral?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(1), pages 269-327.
    10. 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.
    11. Zacharias Maniadis & Fabio Tufano & John A. List, 2017. "To Replicate or Not To Replicate? Exploring Reproducibility in Economics through the Lens of a Model and a Pilot Study," Economic Journal, Royal Economic Society, vol. 127(605), pages 209-235, October.
    12. 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.
    13. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters, in: Essays in the Economics of Crime and Punishment, pages 1-54, National Bureau of Economic Research, Inc.
    14. Nicholas Swanson & Garret Christensen & Rebecca Littman & David Birke & Edward Miguel & Elizabeth Levy Paluck & Zenan Wang, 2020. "Research Transparency Is on the Rise in Economics," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 61-65, May.
    15. T. D. Stanley, 2008. "Meta‐Regression Methods for Detecting and Estimating Empirical Effects in the Presence of Publication Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(1), pages 103-127, February.
    16. 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.
    17. Tomáš Havránek & T. D. Stanley & Hristos Doucouliagos & Pedro Bom & Jerome Geyer‐Klingeberg & Ichiro Iwasaki & W. Robert Reed & Katja Rost & R. C. M. van Aert, 2020. "Reporting Guidelines For Meta‐Analysis In Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 469-475, July.
    18. Mueller-Langer, Frank & Fecher, Benedikt & Harhoff, Dietmar & Wagner, Gert G., 2019. "Replication studies in economics—How many and which papers are chosen for replication, and why?," Research Policy, Elsevier, vol. 48(1), pages 62-83.
    19. Stefano DellaVigna & Elizabeth Linos, 2022. "RCTs to Scale: Comprehensive Evidence From Two Nudge Units," Econometrica, Econometric Society, vol. 90(1), pages 81-116, January.
    20. Andrew C. Chang & Phillip Li, 2022. "Is Economics Research Replicable? Sixty Published Papers From Thirteen Journals Say “Often Notâ€," Critical Finance Review, now publishers, vol. 11(1), pages 185-206, February.
    21. 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.
    22. David Card & Stefano DellaVigna, 2020. "What Do Editors Maximize? Evidence from Four Economics Journals," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 195-217, March.
    23. Bruns, Stephan B. & Asanov, Igor & Bode, Rasmus & Dunger, Melanie & Funk, Christoph & Hassan, Sherif M. & Hauschildt, Julia & Heinisch, Dominik & Kempa, Karol & König, Johannes & Lips, Johannes & Verb, 2019. "Reporting errors and biases in published empirical findings: Evidence from innovation research," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    24. David Card & Stefano DellaVigna, 2013. "Nine Facts about Top Journals in Economics," Journal of Economic Literature, American Economic Association, vol. 51(1), pages 144-161, March.
    25. Zacharias Maniadis & Fabio Tufano & John A. List, 2017. "To Replicate or Not To Replicate? Exploring Reproducibility in Economics through the Lens of a Model and a Pilot Study," Economic Journal, Royal Economic Society, vol. 127(605), pages 209-235, October.
    26. Feige, Edgar L, 1975. "The Consequences of Journal Editorial Policies and a Suggestion for Revision," Journal of Political Economy, University of Chicago Press, vol. 83(6), pages 1291-1295, December.
    27. Cristina Blanco-Perez & Abel Brodeur, 2019. "Transparency in empirical economic research," IZA World of Labor, Institute of Labor Economics (IZA), pages 467-467, November.
    28. Furukawa, Chishio, 2019. "Publication Bias under Aggregation Frictions: Theory, Evidence, and a New Correction Method," EconStor Preprints 194798, ZBW - Leibniz Information Centre for Economics.
    29. Daniel S. Hamermesh, 2017. "Replication in Labor Economics: Evidence from Data, and What It Suggests," American Economic Review, American Economic Association, vol. 107(5), pages 37-40, May.
    30. 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.
    31. 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.
    32. 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.
    33. Camerer, Colin & Dreber, Anna & Forsell, Eskil & Ho, Teck-Hua & Huber, Jurgen & Johannesson, Magnus & Kirchler, Michael & Almenberg, Johan & Altmejd, Adam & Chan, Taizan & Heikensten, Emma & Holzmeist, 2016. "Evaluating replicability of laboratory experiments in Economics," MPRA Paper 75461, University Library of Munich, Germany.
    34. 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.
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    2. Ankel-Peters, Jörg & Fiala, Nathan & Neubauer, Florian, 2023. "Do economists replicate?," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 219-232.

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    More about this item

    Keywords

    p-Hacking; Publication Bias; Data and Code Availability; Data Sharing Policy; Administrative Data; Survey Data;
    All these keywords.

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • 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
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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