| 1. |
- Brütt, Katharina, et al.
(författare)
-
Competition and moral behavior: A meta-analysis of forty-five crowd-sourced experimental designs
- 2023
-
Ingår i: Proceedings of the National Academy of Sciences - PNAS. - : National Academy of Sciences. - 1091-6490 .- 0027-8424. ; 120:23
-
Tidskriftsartikel (refereegranskat)abstract
- Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity-variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find substantial design heterogeneity-estimated to be about 1.6 times as large as the average standard error of effect size estimates of the 45 research designs-indicating that the informativeness and generalizability of results based on a single experimental design are limited. Drawing strong conclusions about the underlying hypotheses in the presence of substantive design heterogeneity requires moving toward much larger data collections on various experimental designs testing the same hypothesis.
|
|
| 2. |
- Menkveld, Albert J., et al.
(författare)
-
Non-Standard Errors
- 2021
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In statistics, samples are drawn from a population in a data generating process (DGP). Standard errors measure the uncertainty in sample 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. 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.
|
|
| 3. |
- Menkveld, Albert J., et al.
(författare)
-
Non-Standard Errors
- 2024
-
Ingår i: Journal of Finance. - 0022-1082. ; 79:3, s. 2339-2390
-
Tidskriftsartikel (refereegranskat)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—nonstandard 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 more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
|
|
| 4. |
- Menkveld, Albert J., et al.
(författare)
-
Nonstandard Errors
- 2024
-
Ingår i: Journal of Finance. - : Wiley-Blackwell. - 1540-6261 .- 0022-1082. ; 79:3, s. 2339-2390
-
Tidskriftsartikel (refereegranskat)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—nonstandard 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 more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
|
|
| 5. |
- Pérignon, Christophe, et al.
(författare)
-
Reproducibility of Empirical Results : Evidence from 1,000 Tests in Finance
- 2022
-
Ingår i: SSRN Electronic Journal. - Paris : HEC Paris. - 1556-5068.
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We analyze the computational reproducibility of more than 1,000 empirical answers to six research questions in finance provided by 168 international research teams. Surprisingly, neither researcher seniority, nor the quality of the research paper seem related to the level of reproducibility. Moreover, researchers exhibit strong overconfidence when assessing the reproducibility of their own research and underestimate the difficulty faced by their peers when attempting to reproduce their results. We further find that reproducibility is higher for researchers with better coding skills and for those exerting more effort. It is lower for more technical research questions and more complex code
|
|
