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Identifying Assumptions and Research Dynamics

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  • Andrew Ellis
  • Ran Spiegler

Abstract

A representative researcher pursuing a question has repeated opportunities for empirical research. To process findings, she must impose an identifying assumption, which ensures that repeated observation would provide a definitive answer to her question. Research designs vary in quality and are implemented only when the assumption is plausible enough according to a KL-divergence-based criterion, and then beliefs are Bayes-updated as if the assumption were perfectly valid. We study the dynamics of this learning process and its induced long-run beliefs. The rate of research cannot uniformly accelerate over time. We characterize environments in which it is stationary. Long-run beliefs can exhibit history-dependence. We apply the model to stylized examples of empirical methodologies: experiments, causal-inference techniques, and (in an extension) ``structural'' identification methods such as ``calibration'' and ``Heckman selection.''

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  • Andrew Ellis & Ran Spiegler, 2024. "Identifying Assumptions and Research Dynamics," Papers 2402.18713, arXiv.org.
  • Handle: RePEc:arx:papers:2402.18713
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    References listed on IDEAS

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    1. Fudenberg, Drew & Romanyuk, Gleb & Strack, Philipp, 2017. "Active learning with a misspecified prior," Theoretical Economics, Econometric Society, vol. 12(3), September.
    2. Ignacio Esponda & Demian Pouzo, 2016. "Berk–Nash Equilibrium: A Framework for Modeling Agents With Misspecified Models," Econometrica, Econometric Society, vol. 84, pages 1093-1130, May.
    3. Ran Spiegler, 2016. "Bayesian Networks and Boundedly Rational Expectations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(3), pages 1243-1290.
    4. Mira Frick & Ryota Iijima & Yuhta Ishii, 2020. "Misinterpreting Others and the Fragility of Social Learning," Econometrica, Econometric Society, vol. 88(6), pages 2281-2328, November.
    5. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    6. 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.
    7. Isaiah Andrews & Jesse M. Shapiro, 2021. "A Model of Scientific Communication," Econometrica, Econometric Society, vol. 89(5), pages 2117-2142, September.
    8. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    9. Ran Spiegler, 2020. "Behavioral Implications of Causal Misperceptions," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 81-106, August.
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