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Non-standard errors

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Menkveld, AJ 
Dreber, A 
Holzmeister, F 
Huber, J 
Johannesson, M 

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.

Description

Keywords

38 Economics, 3801 Applied Economics

Journal Title

The Journal of Finance

Conference Name

Journal ISSN

0022-1082
1540-6261

Volume Title

Publisher

Wiley
Sponsorship
The coordinators are grateful for financial support from (Dreber) the Knut and Al ice Wallenberg Foundation, the Marianne, Marcus Wallenberg Foundation, the Jan Wallander, Tom Hedelius Foundation, (Huber) an FWF grant P29362, (Huber and Kirchler) FWF SFB F63, (Johannesson) Riksbankens Jubileumsfond grant P21-0168, and (Menkveld) NWO-Vici.