| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w23232 |
| 来源ID | Working Paper 23232 |
| Poorly Measured Confounders are More Useful on the Left Than on the Right | |
| Zhuan Pei; Jörn-Steffen Pischke; Hannes Schwandt | |
| 发表日期 | 2017-03-13 |
| 出版年 | 2017 |
| 语种 | 英语 |
| 摘要 | Researchers frequently test identifying assumptions in regression based research designs (which include instrumental variables or difference-in-differences models) by adding additional control variables on the right hand side of the regression. If such additions do not affect the coefficient of interest (much) a study is presumed to be reliable. We caution that such invariance may result from the fact that the observed variables used in such robustness checks are often poor measures of the potential underlying confounders. In this case, a more powerful test of the identifying assumption is to put the variable on the left hand side of the candidate regression. We provide derivations for the estimators and test statistics involved, as well as power calculations, which can help applied researchers interpret their findings. We illustrate these results in the context of various strategies which have been suggested to identify the returns to schooling. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w23232 |
| 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/580906 |
| 推荐引用方式 GB/T 7714 | Zhuan Pei,Jörn-Steffen Pischke,Hannes Schwandt. Poorly Measured Confounders are More Useful on the Left Than on the Right. 2017. |
| 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 | ||
| w23232.pdf（759KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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