No full text
Available on ORBilu since
01 March 2023
Eprint already available on another site (E-prints, Working papers and Research blog)
Non-Standard Errors
Menkveld, Albert; Dreber, Anna; Holzmeister, Felix et al.


Full Text
There are no file associated with this item.

Send to


Keywords :
non-standard errors; multi-analyst approach; liquidity
Abstract :
[en] 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.
Disciplines :
Author, co-author :
Menkveld, Albert
Dreber, Anna
Holzmeister, Felix
Huber, Jürgen
Johannesson, Magnus
Kirchler, Michael
Razen, Michael
Weitzel, Utz
Stefanova, Denitsa ;  University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF)
Language :
Title :
Non-Standard Errors
Publication date :
Focus Area :


Number of views
23 (1 by Unilu)
Number of downloads
0 (0 by Unilu)


Similar publications

Contact ORBilu