| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP15175 |
| DP15175 Signaling, Random Assignment, and Causal Effect Estimation | |
| Gilles Chemla; Christopher Hennessy | |
| 发表日期 | 2020-08-17 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | Causal evidence from random assignment has been labeled "the most credible." We argue it is generally incomplete in finance/economics, omitting central parts of the true empirical causal chain. Random assignment, in eliminating self-selection, simultaneously precludes signaling via treatment choice. However, outside experiments, agents enjoy discretion to signal, thereby caus- ing changes in beliefs and outcomes. Therefore, if the goal is informing discretionary decisions, rather than predicting outcomes after forced/mistaken actions, randomization is problematic. As shown, signaling can amplify, attenuate, or reverse signs of causal e¤ects. Thus, traditional methods of empirical finance, e.g. event studies, are often more credible/useful. |
| 主题 | Development Economics ; Financial Economics ; Industrial Organization ; Labour Economics ; Public Economics |
| 关键词 | Signal Random assignment Causal effect Selection investment Corporate finance Ceo Household finance Government policy |
| URL | https://cepr.org/publications/dp15175 |
| 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/544145 |
| 推荐引用方式 GB/T 7714 | Gilles Chemla,Christopher Hennessy. DP15175 Signaling, Random Assignment, and Causal Effect Estimation. 2020. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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