IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2508.20069.html
   My bibliography  Save this paper

There must be an error here! Experimental evidence on coding errors' biases

Author

Listed:
  • Bruno Ferman
  • Lucas Finamor

Abstract

Quantitative research relies heavily on coding, and coding errors are relatively common even in published research. In this paper, we examine whether individuals are more or less likely to check their code depending on the results they obtain. We test this hypothesis in a randomized experiment embedded in the recruitment process for research positions at a large international economic organization. In a coding task designed to assess candidates' programming abilities, we randomize whether participants obtain an expected or unexpected result if they commit a simple coding error. We find that individuals are almost 20% more likely to detect coding errors when they lead to unexpected results. This asymmetry in error detection depending on the results they generate suggests that coding errors may lead to biased findings in scientific research.

Suggested Citation

  • Bruno Ferman & Lucas Finamor, 2025. "There must be an error here! Experimental evidence on coding errors' biases," Papers 2508.20069, arXiv.org, revised Sep 2025.
  • Handle: RePEc:arx:papers:2508.20069
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2508.20069
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Thomas Herndon & Michael Ash & Robert Pollin, 2014. "Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 38(2), pages 257-279.
    3. Abhijit V. Banerjee & Shawn Cole & Esther Duflo & Leigh Linden, 2007. "Remedying Education: Evidence from Two Randomized Experiments in India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1235-1264.
    4. Richard Anderson & William Greene & B. D. McCullough & H. D. Vinod, 2008. "The role of data/code archives in the future of economic research," Journal of Economic Methodology, Taylor & Francis Journals, vol. 15(1), pages 99-119.
    5. 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.
    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. 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.
    8. Dewald, William G & Thursby, Jerry G & Anderson, Richard G, 1986. "Replication in Empirical Economics: The Journal of Money, Credit and Banking Project," American Economic Review, American Economic Association, vol. 76(4), pages 587-603, September.
    9. 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.
    10. Esther Duflo & Pascaline Dupas & Michael Kremer, 2011. "Peer Effects, Teacher Incentives, and the Impact of Tracking: Evidence from a Randomized Evaluation in Kenya," American Economic Review, American Economic Association, vol. 101(5), pages 1739-1774, August.
    11. Orley Ashenfelter & Michael Greenstone, 2004. "Estimating the Value of a Statistical Life: The Importance of Omitted Variables and Publication Bias," American Economic Review, American Economic Association, vol. 94(2), pages 454-460, May.
    12. Brodeur, Abel & Mikola, Derek & Cook, Nikolai & Brailey, Thomas & Briggs, Ryan & de Gendre, Alexandra & Dupraz, Yannick & Fiala, Lenka & Gabani, Jacopo & Gauriot, Romain & Haddad, Joanne & McWay, Ryan, 2024. "Mass Reproducibility and Replicability: A New Hope," I4R Discussion Paper Series 107, The Institute for Replication (I4R).
    13. Carmen M. Reinhart & Kenneth S. Rogoff, 2010. "Growth in a Time of Debt," American Economic Review, American Economic Association, vol. 100(2), pages 573-578, May.
    14. Daniel S. Hamermesh, 2007. "Viewpoint: Replication in economics," Canadian Journal of Economics, Canadian Economics Association, vol. 40(3), pages 715-733, August.
    15. Stefano DellaVigna & Elizabeth Linos, 2022. "RCTs to Scale: Comprehensive Evidence From Two Nudge Units," Econometrica, Econometric Society, vol. 90(1), pages 81-116, January.
    16. Felix Chopra & Ingar Haaland & Christopher Roth & Andreas Stegmann, 2024. "The Null Result Penalty," The Economic Journal, Royal Economic Society, vol. 134(657), pages 193-219.
    17. Christophe Pérignon & Olivier Akmansoy & Christophe Hurlin & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Albert J Menkveld & Michael Razen & Utz Weitzel, 2024. "Computational Reproducibility in Finance: Evidence from 1,000 Tests," The Review of Financial Studies, Society for Financial Studies, vol. 37(11), pages 3558-3593.
    18. 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.
    19. De Long, J Bradford & Lang, Kevin, 1992. "Are All Economic Hypotheses False?," Journal of Political Economy, University of Chicago Press, vol. 100(6), pages 1257-1272, December.
    20. Ankel-Peters, Jörg & Fiala, Nathan & Neubauer, Florian, 2023. "Do economists replicate?," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 219-232.
    21. Kevin Lang, 2025. "How Credible Is the Credibility Revolution?," Journal of Labor Economics, University of Chicago Press, vol. 43(2), pages 635-663.
    22. Leamer, Edward E & Leonard, Herman B, 1983. "Reporting the Fragility of Regression Estimates," The Review of Economics and Statistics, MIT Press, vol. 65(2), pages 306-317, May.
    23. 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.
    24. 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.
    25. 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.
    26. Orley Ashenfelter & Colm Harmon & Hessel Oosterbeek, 1999. "A Review of Estimates of the Schooling/Earnings Relationship, with Tests for Publication Bias," Working Papers 804, Princeton University, Department of Economics, Industrial Relations Section..
    27. McCullough, B. D. & McGeary, Kerry Anne & Harrison, Teresa D., 2006. "Lessons from the JMCB Archive," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(4), pages 1093-1107, June.
    28. 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.
    29. Orley Ashenfelter & Michael Greenstone, 2004. "Estimating the Value of a Statistical Life: The Importance of Omitted Variables and Publication Bias," American Economic Review, American Economic Association, vol. 94(2), pages 454-460, May.
    30. Ashenfelter, Orley & Harmon, Colm & Oosterbeek, Hessel, 1999. "A review of estimates of the schooling/earnings relationship, with tests for publication bias," Labour Economics, Elsevier, vol. 6(4), pages 453-470, November.
    31. Orley Ashenfelter & Michael Greenstone, 2004. "Estimating the Value of a Statistical Life: The Importance of Omitted Variables and Publication Bias," Working Papers 858, Princeton University, Department of Economics, Industrial Relations Section..
    32. 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.
    33. T. D. Stanley, 2005. "Beyond Publication Bias," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 309-345, July.
    34. repec:ejw:journl:v:4:y:2007:i:3:p:326-337 is not listed on IDEAS
    35. repec:fth:prinin:425 is not listed on IDEAS
    36. 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.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. 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.
    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. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    10. repec:osf:metaar:xq9nt_v1 is not listed on IDEAS
    11. Christopher Snyder & Ran Zhuo, 2018. "Sniff Tests as a Screen in the Publication Process: Throwing out the Wheat with the Chaff," NBER Working Papers 25058, National Bureau of Economic Research, Inc.
    12. Sebastian Gechert & Tomas Havranek & Zuzana Irsova & Dominika Kolcunova, 2022. "Measuring Capital-Labor Substitution: The Importance of Method Choices and Publication Bias," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 55-82, July.
    13. 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.
    14. repec:osf:metaar:nshqx_v1 is not listed on IDEAS
    15. Havranek, Tomas & Horvath, Roman & Irsova, Zuzana & Rusnak, Marek, 2015. "Cross-country heterogeneity in intertemporal substitution," Journal of International Economics, Elsevier, vol. 96(1), pages 100-118.
    16. Costanza Naguib, 2024. "P-hacking and Significance Stars," Diskussionsschriften dp2409, Universitaet Bern, Departement Volkswirtschaft.
    17. Furukawa, Chishio, 2019. "Publication Bias under Aggregation Frictions: Theory, Evidence, and a New Correction Method," EconStor Preprints 194798, ZBW - Leibniz Information Centre for Economics.
    18. 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.
    19. Tomas Havranek, 2013. "Publication Bias in Measuring Intertemporal Substitution," Working Papers IES 2013/15, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2013.
    20. repec:osf:metaar:9a3rw_v1 is not listed on IDEAS
    21. Tomas Havranek & Anna Sokolova, 2016. "Do Consumers Really Follow a Rule of Thumb? Three Thousand Estimates from 130 Studies Say "Probably Not"," Working Papers 2016/08, Czech National Bank, Research and Statistics Department.
    22. Balafoutas, Loukas & Celse, Jeremy & Karakostas, Alexandros & Umashev, Nicholas, 2025. "Incentives and the replication crisis in social sciences: A critical review of open science practices," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 114(C).
    23. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, Institute of Labor Economics (IZA).

    More about this item

    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:arx:papers:2508.20069. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.