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Persuasion Bias in Science: Can Economics Help?

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Listed:
  • 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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    Cited by:

    1. Eliaz, Kfir & Spiegler, Ran & Weiss, Yair, 2019. "Cheating with (recursive) models," CEPR Discussion Papers 14100, C.E.P.R. Discussion Papers.
    2. 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.
    3. 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.
    4. Herresthal, C., 2017. "Hidden Testing and Selective Disclosure of Evidence," Cambridge Working Papers in Economics 1712, Faculty of Economics, University of Cambridge.
    5. 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).
    6. Maximilian Kasy & Jann Spiess, 2022. "Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability," Papers 2208.09638, arXiv.org, revised Oct 2023.
    7. Dahm, Matthias & González, Paula & Porteiro, Nicolás, 2018. "The enforcement of mandatory disclosure rules," Journal of Public Economics, Elsevier, vol. 167(C), pages 21-32.
    8. 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.
    9. 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.
    10. Felgenhauer, Mike, 2021. "Experimentation and manipulation with preregistration," Games and Economic Behavior, Elsevier, vol. 130(C), pages 400-408.
    11. Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers CWP50/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Alonso, Ricardo & Câmara, Odilon, 2021. "Organizing Data Analytics," CEPR Discussion Papers 16768, C.E.P.R. Discussion Papers.
    13. 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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