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| 教育研究中的双重稳健估计× | 双重差分法 (Diff-in-Diff)× | |
|---|---|---|
| 领域≠ | 因果推断 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1994-2005 | 1994 |
| 提出者≠ | Robins, Rotnitzky & Zhao (1994); Bang & Robins (2005) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| 类型≠ | Causal inference / semiparametric estimator | Causal inference / panel regression |
| 开创性文献≠ | Bang, H., & Robins, J. M. (2005). Doubly Robust Estimation in Missing Data and Causal Inference Models. Biometrics, 61(4), 962-973. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 别名≠ | DR estimator in education, AIPW in education, augmented IPW in education research, doubly robust causal estimation for educational outcomes | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| 相关≠ | 6 | 5 |
| 摘要≠ | Doubly robust estimation (DR) is a semiparametric causal inference approach that combines an outcome regression model with a propensity score model. In education research, it is used to estimate the causal effect of educational programs, interventions, or policies on student outcomes when treatment assignment is non-random but observed covariates can account for selection bias. The estimator is consistent if either — not necessarily both — of the two component models is correctly specified. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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