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Effectiveness of ex ante honesty oaths in reducing dishonesty depends on content

Nature Human Behaviour volume 9, pages 169–187 (2025)Cite this article

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Abstract

Dishonest behaviours such as tax evasion impose significant societal costs. Ex ante honesty oaths—commitments to honesty before action—have been proposed as interventions to counteract dishonest behaviour, but the heterogeneity in findings across operationalizations calls their effectiveness into question. We tested 21 honesty oaths (including a baseline oath)—proposed, evaluated and selected by 44 expert researchers—and a no-oath condition in a megastudy involving 21,506 UK and US participants from Prolific.com who played an incentivized tax evasion game online. Of the 21 interventions, 10 significantly improved tax compliance by 4.5 to 8.5 percentage points, with the most successful nearly halving tax evasion. Limited evidence for moderators was found. Experts and laypeople failed to predict the most effective interventions, though experts’ predictions were more accurate. In conclusion, honesty oaths were effective in curbing dishonesty, but their effectiveness varied depending on content. These findings can help design impactful interventions to curb dishonesty.

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Fig. 1: Study objectives.
Fig. 2: Experimental design and tax evasion game.
Fig. 3: Average marginal effects of honesty oath interventions.
Fig. 4: Average marginal effects depending on the type of intervention focus and dishonesty justification.
Fig. 5: Recommendations for effective ex ante honesty oath interventions.

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Data availability

The datasets generated by the survey research and/or analysed during the current study are available via Zenodo at https://doi.org/10.5281/zenodo.13329833 (ref. 80) and at https://osf.io/t3sm4/ (pilot studies)81.

Code availability

All code used to generate the main and supplementary analyses is available in the osf.io repository at https://osf.io/t3sm4/ and via Zenodo at https://doi.org/10.5281/zenodo.13329833 (ref. 80). We used R (version 4.2.1; ref. 82) and the R packages broom (version 1.0.4; ref. 83), dplyr (version 1.1.1; ref. 84), ggplot2 (version 3.4.4; ref. 85), ggpubr (version 0.4.0; ref. 86), glmmTMB (version 1.1.7; ref. 87), janitor (version 2.1.0; ref. 88), lme4 (version 1.1-32; ref. 89), marginaleffects (version 0.14.0; ref. 90), meta.shrinkage (version 0.1.4; ref. 91), papaja (version 0.1.1; ref. 92), purrr (version 1.0.1; ref. 93), psych (version 2.2.5; ref. 94), qualtRics (version 3.1.7; ref. 95), sjPlot (version 2.8.14; ref. 96), stringr (version 1.5.0; ref. 97), tidyverse (version 1.3.2; ref. 98), TOSTER (version 0.8.0; ref. 38) and mice (version 3.16.0; ref. 99) for our analyses.

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Acknowledgements

P.M. was supported by grant no. AUFF-E-2019-9-4 NOVA. Y.F. was supported by ERC grant no. 101054656 (project acronym VCOMP). E.P. and Y.F. were supported by a grant from the Israeli Science Foundation Award No. 385/20. A.Z.C. was supported by grant no. 2018/30/E/HS6/00863 from the National Science Center, Poland. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank P. Nickl for input on visualizations.

Author information

Authors and Affiliations

  1. Department of Management, Aarhus University, Aarhus, Denmark

    Janis H. Zickfeld, Christian T. Elbæk, Mathilde H. Tønnesen & Panagiotis Mitkidis

  2. Department of Psychology and Behavioural Sciences, Aarhus University, Aarhus, Denmark

    Karolina A. Ścigała, Laila Nockur, Yngwie Asbjørn Nielsen & Stefan Pfattheicher

  3. Department of Philosophy, University of Milan, Milan, Italy

    John Michael

  4. Department of Philosophy and Religious Studies, NTNU Trondheim, Trondheim, Norway

    Gabriel Levy

  5. Baruch Ivcher School of Psychology, Reichman University, Herzliya, Israel

    Shahar Ayal

  6. Max Planck Institute for the Study of Crime, Security and Law, Freiburg, Germany

    Isabel Thielmann & Alicia Seidl

  7. Federmann School of Public Policy, Hebrew University of Jerusalem, Jerusalem, Israel

    Eyal Peer & Ronit Montal-Rosenberg

  8. Department of Psychology, University of Milan Bicocca, Milan, Italy

    Valerio Capraro

  9. Department of Business Administration, Ben-Gurion University of the Negev, Beersheba, Israel

    Rachel Barkan

  10. Department of Strategy and Management, Norwegian School of Economics, Bergen, Norway

    Simen Bø & Jareef Bin Martuza

  11. Department of Management, Prague University of Economics and Business, Prague, Czech Republic

    Štěpán Bahník

  12. Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark

    Daniele Nosenzo

  13. Max Planck Institute for Human Development, Berlin, Germany

    Ralph Hertwig, Nils Köbis, Jan K. Woike & Zoe Rahwan

  14. Questrom School of Business, Boston University, Boston, MA, USA

    Nina Mazar

  15. Department of Psychology, Bielefeld University, Bielefeld, Germany

    Alexa Weiss

  16. Institute of Environmental Planning, Leibniz University Hannover, Hannover, Germany

    Ann-Kathrin Koessler

  17. IESE Business School, University of Navarra, Barcelona, Spain

    Sebastian Hafenbrädl

  18. School of Psychology, University of Plymouth, Plymouth, UK

    Patricia Kanngiesser & Jan K. Woike

  19. Federal University of Applied Administrative Sciences, Berlin, Germany

    Simon Schindler

  20. Fresenius University, Hamburg, Germany

    Philipp Gerlach

  21. Center for Trustworthy Data Science and Security, University of Duisburg-Essen, Duisburg, Germany

    Nils Köbis

  22. Paris School of Economics, Paris, France

    Nicolas Jacquemet

  23. CES, Université Paris 1 Panthéon-Sorbonne, Paris, France

    Nicolas Jacquemet

  24. Faculty of Social Sciences, Charles University, Prague, Czech Republic

    Marek Vranka

  25. Fuqua School of Busisness, Duke University, Durham, NC, USA

    Dan Ariely

  26. Faculty of Law, Bar Ilan University, Ramat Gan, Israel

    Yuval Feldman

  27. Institute of Psychology, University of Wrocław, Wrocław, Poland

    Michał Białek

  28. Department of Psychology, University of Kaiserslautern-Landau, Landau, Germany

    Alicia Seidl

  29. Batten School of Leadership and Public Policy, University of Virginia, Charlottesville, VA, USA

    Eileen Chou

  30. Department of Economics, Management, and Quantitative Methods, University of Milan, Milan, Italy

    Agne Kajackaite

  31. Institute of Economics, Ulm University, Ulm, Germany

    Simeon Schudy

  32. CESifo Munich, Munich, Germany

    Simeon Schudy & Ulrich Glogowsky

  33. Department of Economics, Johannes Kepler University Linz, Linz, Austria

    Ulrich Glogowsky

  34. Jagiellonian University, Krakow, Poland

    Anna Z. Czarna

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  1. Janis H. Zickfeld
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  4. John Michael
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Contributions

Conceptualization: J.H.Z. and P.M. Data curation: J.H.Z. Formal analysis: J.H.Z. Funding acquisition: J.M., D.A., I.T., S.H., A.-K.K., S.P. and P.M. Investigation: J.H.Z. Methodology: J.H.Z., K.A.Ś., C.T.E., J.M., M.H.T., G.L., S.A., E.P., E.C., U.G., S. Schudy, Y.F., P.K., N.M., S. Schindler, A.W., D.N., V.C., R.H., R.B., D.A., R.M.-R., I.T., J.B.M., P.G., Š.B., M.B., J.K.W., L.N., S.B., N.J., N.K., S.H., Z.R., A.K., Y.A.N., A.-K.K., M.V., A.Z.C., A.S., S.P. and P.M. Project administration: J.H.Z. Validation: J.H.Z., E.P., J.B.M. and Y.A.N. Visualization: J.H.Z. and Z.R. Writing—original draft: J.H.Z. Writing—review and editing: J.H.Z., K.A.Ś., C.T.E., J.M., M.H.T., G.L., S.A., E.P., E.C., U.G., S. Schudy, Y.F., P.K., N.M., S. Schindler, A.W., D.N., V.C., R.H., R.B., D.A., R.M.-R., I.T., J.B.M., P.G., Š.B., M.B., J.K.W., L.N., S.B., N.J., N.K., S.H., Z.R., A.K., Y.A.N., A.-K.K., M.V., A.Z.C., A.S., S.P. and P.M. The authorship order for the first seven and last two authors was set a priori. The authorship order for the remaining authors was determined randomly.

Corresponding author

Correspondence to Janis H. Zickfeld.

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Nature Human Behaviour thanks Christoph Bühren, Shaul Shalvi and Jan Voelkel for their contribution to the peer review of this work. Peer reviewer reports are available.

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Supplementary Notes 1–23, Figs. 1–40 and Tables 1–66.

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Zickfeld, J.H., Ścigała, K.A., Elbæk, C.T. et al. Effectiveness of ex ante honesty oaths in reducing dishonesty depends on content. Nat Hum Behav 9, 169–187 (2025). https://doi.org/10.1038/s41562-024-02009-0

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