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Persuasion Bias in Science: Can Economics Help?

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  • Alfredo Di Tillio
  • Marco Ottaviani
  • Peter Norman Sørensen

Abstract

We investigate the impact of conflicts of interests on randomised controlled trials in a game‐theoretic framework. A researcher seeks to persuade an evaluator that the causal effect of a treatment outweighs its cost, to justify acceptance. The researcher can use private information to manipulate the experiment in three alternative ways: (i) sampling subjects based on their treatment effect, (ii) assigning subjects to treatment based on their baseline outcome, or (iii) selectively reporting experimental outcomes. The resulting biases have different welfare implications: for sufficiently high acceptance cost, in our binary illustration the evaluator loses in cases (i) and (iii) but benefits in case (ii).

Suggested Citation

  • Alfredo Di Tillio & Marco Ottaviani & Peter Norman Sørensen, 2017. "Persuasion Bias in Science: Can Economics Help?," Economic Journal, Royal Economic Society, vol. 127(605), pages 266-304, October.
    • Handle: RePEc:wly:econjl:v:127:y:2017:i:605:p:f266-f304
    DOI: 10.1111/ecoj.12515
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    1. Charles F. Manski, 2013. "Response to the Review of ‘Public Policy in an Uncertain World’," Economic Journal, Royal Economic Society, vol. 0, pages 412-415, August.
    2. Dahm, Matthias & González, Paula & Porteiro, Nicolás, 2009. "Trials, tricks and transparency: How disclosure rules affect clinical knowledge," Journal of Health Economics, Elsevier, vol. 28(6), pages 1141-1153, December.
    3. Emeric Henry, 2009. "Strategic Disclosure of Research Results: The Cost of Proving Your Honesty," Economic Journal, Royal Economic Society, vol. 119(539), pages 1036-1064, July.
    4. Mario Forni & Luca Gambetti & Marco Lippi & Luca Sala, 2017. "Noise Bubbles," Economic Journal, Royal Economic Society, vol. 127(604), pages 1940-1976, September.
    5. Emir Kamenica & Matthew Gentzkow, 2011. "Bayesian Persuasion," American Economic Review, American Economic Association, vol. 101(6), pages 2590-2615, October.
    6. Anton Kolotilin & Tymofiy Mylovanov & Andriy Zapechelnyuk & Ming Li, 2017. "Persuasion of a Privately Informed Receiver," Econometrica, Econometric Society, vol. 85(6), pages 1949-1964, November.
    7. Hunt Allcott, 2015. "Site Selection Bias in Program Evaluation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(3), pages 1117-1165.
    8. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-127, February.
    9. 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.
    10. Luis Rayo & Ilya Segal, 2010. "Optimal Information Disclosure," Journal of Political Economy, University of Chicago Press, vol. 118(5), pages 949-987.
    11. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    12. Isabelle Brocas & Juan D. Carrillo, 2007. "Influence through ignorance," RAND Journal of Economics, RAND Corporation, vol. 38(4), pages 931-947, December.
    13. Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers CWP50/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Nicola Lacetera & Lorenzo Zirulia, 2011. "The Economics of Scientific Misconduct," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 27(3), pages 568-603.
    15. Manski, Charles F., 2013. "Public Policy in an Uncertain World: Analysis and Decisions," Economics Books, Harvard University Press, number 9780674066892, march.
    16. Luke Holman & Megan L Head & Robert Lanfear & Michael D Jennions, 2015. "Evidence of Experimental Bias in the Life Sciences: Why We Need Blind Data Recording," PLOS Biology, Public Library of Science, vol. 13(7), pages 1-12, July.
    17. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    18. Mike Felgenhauer & Elisabeth Schulte, 2014. "Strategic Private Experimentation," American Economic Journal: Microeconomics, American Economic Association, vol. 6(4), pages 74-105, November.
    19. Jacob Glazer & Ariel Rubinstein, 2004. "On Optimal Rules of Persuasion," Econometrica, Econometric Society, vol. 72(6), pages 1715-1736, November.
    20. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, Enero-Abr.
    21. Zacharias Maniadis & Fabio Tufano & John A. List, 2014. "One Swallow Doesn't Make a Summer: New Evidence on Anchoring Effects," American Economic Review, American Economic Association, vol. 104(1), pages 277-290, January.
    22. Michael J. Fishman & Kathleen M. Hagerty, 1990. "The Optimal Amount of Discretion to Allow in Disclosure," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 105(2), pages 427-444.
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    Cited by:

    1. Maximilian Kasy & Jann Spiess, 2022. "Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability," Papers 2208.09638, arXiv.org, revised Jul 2024.
    2. Eliaz, Kfir & Spiegler, Ran & Weiss, Yair, 2019. "Cheating with (recursive) models," CEPR Discussion Papers 14100, C.E.P.R. Discussion Papers.
    3. Maximilian Kasy & Jann Spiess, 2022. "Rationalizing Pre-Analysis Plans:Statistical Decisions Subject to Implementability," Economics Series Working Papers 975, University of Oxford, Department of Economics.
    4. Michel Abramowicz & Ariane Szafarz, 2019. "Ethics of Randomized Controlled Trials: Should Economists Care about Equipoise?," Working Papers CEB 19-017, ULB -- Universite Libre de Bruxelles.
    5. Herresthal, C., 2017. "Hidden Testing and Selective Disclosure of Evidence," Cambridge Working Papers in Economics 1712, Faculty of Economics, University of Cambridge.
    6. So, Tony, 2020. "Classroom experiments as a replication device," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 86(C).
    7. 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).
    8. Dahm, Matthias & González, Paula & Porteiro, Nicolás, 2018. "The enforcement of mandatory disclosure rules," Journal of Public Economics, Elsevier, vol. 167(C), pages 21-32.
    9. 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.
    10. Jeremy Bertomeu & Davide Cianciaruso, 2018. "Verifiable disclosure," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(4), pages 1011-1044, June.
    11. Ricardo Alonso & Odilon Câmara, 2024. "Organizing Data Analytics," Management Science, INFORMS, vol. 70(5), pages 3123-3143, May.
    12. Felgenhauer, Mike, 2021. "Experimentation and manipulation with preregistration," Games and Economic Behavior, Elsevier, vol. 130(C), pages 400-408.
    13. Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers CWP50/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Beatrice Braut & Matteo Migheli, 2025. "A simple message and two framings to enhance protective behaviours adoption in a pandemic," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 72(1), pages 1-29, June.
    15. Silvia Martinez-Gorricho & Carlos Oyarzun, 2024. "Testing under information manipulation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 77(3), pages 849-890, May.
    16. Herresthal, Claudia, 2022. "Hidden testing and selective disclosure of evidence," Journal of Economic Theory, Elsevier, vol. 200(C).

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General

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