Non-Standard Errors
Date
2024
Authors
Menkveld, A.J.
Dreber, A.
Holzmeister, F.
Huber, J.
Johannesson, M.
Kirchler, M.
Razen, M.
Weitzel, U.
Abad, D.
Abudy, M.M.
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Advisors
Journal Title
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Type:
Journal article
Citation
Journal of Finance, 2024; LXXIX [79](3):2339-2390
Statement of Responsibility
Albert J. Menkveld ... Marta K. Khomyn ... et al.
Conference Name
Abstract
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
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© 2024 The Authors. The Journal of Finance published by Wiley Periodicals LLC on behalf of American Finance Association. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.