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An economic theory of statistical testing

Author

Listed:
  • Aleksey Tetenov

    (Institute for Fiscal Studies and University of Geneva)

Abstract

This paper models the use of statistical hypothesis testing in regulatory approval. A privately informed agent proposes an innovation. Its approval is benefi cial to the proponent, but potentially detrimental to the regulator. The proponent can conduct a costly clinical trial to persuade the regulator. I show that the regulator can screen out all ex-ante undesirable proponents by committing to use a simple statistical test. Its level is the ratio of the trial cost to the proponent's bene fit from approval. In application to new drug approval, this level is around 15% for an average Phase III clinical trial.

Suggested Citation

  • Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers CWP50/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:50/16
    as

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    File URL: https://www.ifs.org.uk/uploads/cemmap/wps/cwp501616.pdf
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    References listed on IDEAS

    as
    1. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.
    2. Tetenov, Aleksey, 2012. "Statistical treatment choice based on asymmetric minimax regret criteria," Journal of Econometrics, Elsevier, vol. 166(1), pages 157-165.
    3. Keisuke Hirano & Jack R. Porter, 2009. "Asymptotics for Statistical Treatment Rules," Econometrica, Econometric Society, vol. 77(5), pages 1683-1701, September.
    4. 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.
    5. Emir Kamenica & Matthew Gentzkow, 2011. "Bayesian Persuasion," American Economic Review, American Economic Association, vol. 101(6), pages 2590-2615, October.
    6. Sylvain Chassang & Gerard Padro I Miquel & Erik Snowberg, 2012. "Selective Trials: A Principal-Agent Approach to Randomized Controlled Experiments," American Economic Review, American Economic Association, vol. 102(4), pages 1279-1309, June.
    7. Charles F. Manski, 2004. "Statistical Treatment Rules for Heterogeneous Populations," Econometrica, Econometric Society, vol. 72(4), pages 1221-1246, July.
    8. DiMasi, Joseph A. & Hansen, Ronald W. & Grabowski, Henry G., 2003. "The price of innovation: new estimates of drug development costs," Journal of Health Economics, Elsevier, vol. 22(2), pages 151-185, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. 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.
    2. Flora C. Shi & Martin J. Wainwright & Stephen Bates, 2025. "Instance-Adaptive Hypothesis Tests with Heterogeneous Agents," Papers 2510.21178, arXiv.org.
    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. Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
    5. Maximilian Kasy & Jann Spiess, 2022. "Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability," Papers 2208.09638, arXiv.org, revised Jul 2024.
    6. Hirano, Keisuke & Porter, Jack R., 2020. "Asymptotic analysis of statistical decision rules in econometrics," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 283-354, Elsevier.
    7. Chiu, Ching-Wai (Jeremy) & Hayes, Simon & Kapetanios, George & Theodoridis, Konstantinos, 2019. "A new approach for detecting shifts in forecast accuracy," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1596-1612.
    8. Alfredo Di Tillio & Marco Ottaviani & Peter Norman Sørensen, 2021. "Strategic Sample Selection," Econometrica, Econometric Society, vol. 89(2), pages 911-953, March.
    9. Furukawa, Chishio, 2019. "Publication Bias under Aggregation Frictions: Theory, Evidence, and a New Correction Method," EconStor Preprints 194798, ZBW - Leibniz Information Centre for Economics.
    10. Charles F. Manski & Aleksey Tetenov, 2019. "Trial Size for Near-Optimal Choice Between Surveillance and Aggressive Treatment: Reconsidering MSLT-II," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 305-311, March.
    11. Alexander Frankel & Maximilian Kasy, 2022. "Which Findings Should Be Published?," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 1-38, February.
    12. Ravi Jagadeesan & Davide Viviano, 2025. "Publication Design with Incentives in Mind," Papers 2504.21156, arXiv.org, revised Sep 2025.
    13. Davide Viviano & Kaspar Wuthrich & Paul Niehaus, 2021. "A model of multiple hypothesis testing," Papers 2104.13367, arXiv.org, revised Feb 2026.

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