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| 稳健模糊断点回归设计× | 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≠ | 2014 (robust CCT estimator); 2001 (fuzzy RDD formalization) | 1994 |
| 提出者≠ | Calonico, Cattaneo, and Titiunik (robust inference framework); Hahn, Todd, and Van der Klaauw (fuzzy RDD formalization) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| 类型≠ | Quasi-experimental causal inference with IV at threshold | Causal inference / panel regression |
| 开创性文献≠ | Calonico, S., Cattaneo, M. D., & Titiunik, R. (2014). Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs. Econometrica, 82(6), 2295-2326. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 别名≠ | Robust Fuzzy RDD, Fuzzy RD with robust inference, bias-corrected fuzzy RD, CCT fuzzy RDD | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| 相关 | 5 | 5 |
| 摘要≠ | Robust Fuzzy Regression Discontinuity Design estimates a local average treatment effect (LATE) at a threshold where crossing the cutoff raises — but does not guarantee — treatment receipt. Introduced by Calonico, Cattaneo, and Titiunik (2014), the robust framework applies bias-corrected local polynomial estimation with a robust variance estimator, correcting the coverage failures of conventional bandwidth-optimal inference in both the sharp and fuzzy cases. | 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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