Non- standard errors

Albert J. Menkveld; Anna Dreber; Felix  Holzmeister; Juergen Huber; Magnus Johannesson; Michael Kirchler; Sebastian Neusüss; Michael Razen; Utz Weitzel; Khaladdin Rzayev; Fincap

Non- standard errors

Albert J. Menkveld, Anna Dreber, Felix Holzmeister, Juergen Huber, Magnus Johannesson, Michael Kirchler, Sebastian Neusüss, Michael Razen, Utz Weitzel, Khaladdin Rzayev, Fincap

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Journal	Journal of Finance
Publication status	Accepted/In press - 15 Feb 2023

Cite this

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title = "Non- standard errors",

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.",

author = "Menkveld, {Albert J.} and Anna Dreber and Felix Holzmeister and Juergen Huber and Magnus Johannesson and Michael Kirchler and Sebastian Neus{\"u}ss and Michael Razen and Utz Weitzel and Khaladdin Rzayev and Fincap",

year = "2023",

month = feb,

day = "15",

language = "English",

journal = "Journal of Finance",

issn = "0022-1082",

publisher = "Wiley-Blackwell",

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TY - JOUR

T1 - Non- standard errors

AU - Menkveld, Albert J.

AU - Dreber, Anna

AU - Holzmeister, Felix

AU - Huber, Juergen

AU - Johannesson, Magnus

AU - Kirchler, Michael

AU - Neusüss, Sebastian

AU - Razen, Michael

AU - Weitzel, Utz

AU - Rzayev, Khaladdin

AU - Fincap

PY - 2023/2/15

Y1 - 2023/2/15

N2 - 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.

AB - 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.

UR - https://onlinelibrary.wiley.com/journal/15406261

M3 - Article

JO - Journal of Finance

JF - Journal of Finance

SN - 0022-1082

ER -

Non- standard errors

Abstract

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