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Non-standard errors

Bogoev, D.; Karam, A.; et al.

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Authors

Dimitar Bogoev dimitar.bogoev@durham.ac.uk
PGR Student Doctor of Philosophy

et al.



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: Non-standard 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 better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

Citation

Bogoev, D., Karam, A., & et al. (2024). Non-standard errors. Journal of Finance, 79(3), 2339-2390. https://doi.org/10.1111/jofi.13337

Journal Article Type Article
Acceptance Date Feb 14, 2023
Online Publication Date Apr 17, 2024
Publication Date 2024-06
Deposit Date Aug 17, 2023
Publicly Available Date Aug 14, 2024
Journal Journal of Finance
Print ISSN 0022-1082
Electronic ISSN 1540-6261
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 79
Issue 3
Pages 2339-2390
DOI https://doi.org/10.1111/jofi.13337
Public URL https://durham-repository.worktribe.com/output/1720574

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