| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w29702 |
| 来源ID | Working Paper 29702 |
| Incentive-Compatible Critical Values | |
| Adam McCloskey; Pascal Michaillat | |
| 发表日期 | 2022-01-31 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 摘要 | Statistically significant results are more rewarded than insignificant ones, so researchers have the incentive to pursue statistical significance. Such p-hacking reduces the informativeness of hypothesis tests by making significant results much more common than they are supposed to be in the absence of true significance. To address this problem, we construct critical values of test statistics such that, if these values are used to determine significance, and if researchers optimally respond to these new significance standards, then significant results occur with the desired frequency. Such incentive-compatible critical values allow for p-hacking so they are larger than classical critical values. Using evidence from the social and medical sciences, we find that the incentive-compatible critical value for any test and any significance level is the classical critical value for the same test with approximately one fifth of the significance level—a form of Bonferroni correction. For instance, for a z-test with a significance level of 5%, the incentive-compatible critical value is 2.31 instead of 1.65 if the test is one-sided and 2.57 instead of 1.96 if the test is two-sided. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w29702 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/587376 |
| 推荐引用方式 GB/T 7714 | Adam McCloskey,Pascal Michaillat. Incentive-Compatible Critical Values. 2022. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w29702.pdf（475KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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