方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 前门调整（前门准则）× | 工具变量法/两阶段最小二乘法 (IV/2SLS)× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1995 | 2009 |
| 提出者≠ | Judea Pearl | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| 类型≠ | Causal identification (graphical adjustment) | Instrumental-variables regression |
| 开创性文献≠ | Pearl, J. (1995). Causal Diagrams for Empirical Research. Biometrika, 82(4), 669-688. DOI ↗ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 别名≠ | frontdoor criterion, Pearl's frontdoor adjustment, frontdoor formula, Ön Kapı Düzenlemesi (Frontdoor Adjustment) | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| 相关≠ | 4 | 5 |
| 摘要≠ | Frontdoor adjustment is Judea Pearl's graphical identification strategy, introduced in 1995, that recovers the causal effect of a treatment on an outcome through a fully mediating variable even when an unobserved confounder sits between the treatment and the outcome. It is the go-to tool when the backdoor criterion cannot be satisfied because the confounder is unmeasured. | IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009). |
| ScholarGate数据集 ↗ |
|
|