- Albert J. Menkveld et al. Norges Bank co-authors: Saskia Ter Ellen and Hans Christian Wika.
- Working Paper
In statistics, samples are drawn from a population in a datagenerating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidencegenerating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Norges Bank’s working papers present research projects and reports that are generally not in their final form. Other analyses by Norges Bank’s economists are also included in the series. The views and conclusions in these documents are those of the authors.
ISSN 1502-8190 (online)