Nonstandard errors

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Menkveld, Albert J. and et al. (2024) Nonstandard errors. The Journal of Finance, 79 (3). pp. 2339-2390. ISSN 1540-6261

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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.

Item Type:	Article
Additional Information:	Please see the published article for the full author list. Funding information: Knut and Alice Wallenberg Foundation; Marianne, Marcus Wallenberg Foundation; Jan Wallander, Tom Hedelius Foundation; Riksbankens Jubileumsfond. Grant Number: P21-0168; Swedish House of Finance; Dutch Research Council. Grant Number: 016.Vici.185.068; Austrian Science Fund. Grant Numbers: P29362, SFBF63.
Faculty \ School:	Faculty of Social Sciences > Norwich Business School
Related URLs:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	22 Oct 2024 09:30
Last Modified:	14 Nov 2024 00:52
URI:	https://ueaeprints.uea.ac.uk/id/eprint/97091
DOI:	10.1111/jofi.13337

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