| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP16751 |
| DP16751 Non-Standard Errors | |
| Albert J. Menkveld; Anna Dreber; Felix Holzmeister; Juergen Huber; Magnus Johannesson; Michael Kirchler; Sebastian Neusüess; Michael Razen; Utz Weitzel; Christian Wolff | |
| 发表日期 | 2021-11-23 |
| 出版年 | 2021 |
| 语种 | 英语 |
| 摘要 | 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. |
| 主题 | Financial Economics |
| URL | https://cepr.org/publications/dp16751 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/545685 |
| 推荐引用方式 GB/T 7714 | Albert J. Menkveld,Anna Dreber,Felix Holzmeister,et al. DP16751 Non-Standard Errors. 2021. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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