Arbeitspapier
Non-Standard Errors*
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Discussion Paper ; No. 385
- Klassifikation
-
Wirtschaft
Estimation: General
Methodological Issues: General
Econometric and Statistical Methods and Methodology: General
- Thema
-
uncertainty
standard errors
reproducibility
hypotheses
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Bosch-Rosa, Ciril
Kassner, Bernhard
- Ereignis
-
Veröffentlichung
- (wer)
-
Ludwig-Maximilians-Universität München und Humboldt-Universität zu Berlin, Collaborative Research Center Transregio 190 - Rationality and Competition
- (wo)
-
München und Berlin
- (wann)
-
2023
- Handle
- Letzte Aktualisierung
- 10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft.
Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Bosch-Rosa, Ciril
- Kassner, Bernhard
- Ludwig-Maximilians-Universität München und Humboldt-Universität zu Berlin, Collaborative Research Center Transregio 190 - Rationality and Competition
Entstanden
- 2023
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