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A Model of Scientific Communication

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  • Isaiah Andrews
  • Jesse M. Shapiro

Abstract

We propose a positive model of empirical science in which an analyst makes a report to an audience after observing some data. Agents in the audience may differ in their beliefs or objectives, and may therefore update or act differently following a given report. We contrast the proposed model with a classical model of statistics in which the report directly determines the payoff. We identify settings in which the predictions of the proposed model differ from those of the classical model, and seem to better match practice.

Suggested Citation

  • Isaiah Andrews & Jesse M. Shapiro, 2020. "A Model of Scientific Communication," NBER Working Papers 26824, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:26824
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    Cited by:

    1. Christina Korting & Carl Lieberman & Jordan Matsudaira & Zhuan Pei & Yi Shen, 2023. "Visual Inference and Graphical Representation in Regression Discontinuity Designs," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(3), pages 1977-2019.
    2. Alexander Frankel & Maximilian Kasy, 2022. "Which Findings Should Be Published?," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 1-38, February.
    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. Patrick Kline & Evan K. Rose & Christopher R. Walters, 2024. "A Discrimination Report Card," American Economic Review, American Economic Association, vol. 114(8), pages 2472-2525, August.
    5. Maximilian Kasy & Jann Spiess, 2022. "Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability," Papers 2208.09638, arXiv.org, revised Jul 2024.
    6. Marco Stenborg Petterson & David Seim & Jesse M. Shapiro, 2023. "Bounds on a Slope from Size Restrictions on Economic Shocks," American Economic Journal: Microeconomics, American Economic Association, vol. 15(3), pages 552-572, August.
    7. Sihui Zhao & Xinbo Wang & Lin Liu & Xin Zhang, 2024. "Covariate Adjustment in Randomized Experiments Motivated by Higher-Order Influence Functions," Papers 2411.08491, arXiv.org, revised Dec 2024.
    8. Talia Gillis & Bryce McLaughlin & Jann Spiess, 2021. "On the Fairness of Machine-Assisted Human Decisions," Papers 2110.15310, arXiv.org, revised Sep 2023.
    9. Andrew Ellis & Ran Spiegler, 2024. "Identifying Assumptions and Research Dynamics," Papers 2402.18713, arXiv.org.
    10. Davide Viviano & Kaspar Wuthrich & Paul Niehaus, 2021. "A model of multiple hypothesis testing," Papers 2104.13367, arXiv.org, revised Apr 2024.
    11. Claudia Noack, 2021. "Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption," Papers 2106.06421, arXiv.org.
    12. Colo, Philippe, 2021. "Expert-based Knowledge: Communicating over Scientific Models," MPRA Paper 110434, University Library of Munich, Germany.

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    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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