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。
| 动态模糊断点回归设计× | 面板数据回归断点设计× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2001-2010 | 1960 (original RDD); panel extension codified 2000s–2010s |
| 提出者≠ | Cellini, Ferreira & Rothstein (dynamic RDD, 2010); Hahn, Todd & Van der Klaauw (fuzzy RDD foundations, 2001) | Thistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied work |
| 类型≠ | Quasi-experimental causal inference | Causal inference / quasi-experimental |
| 开创性文献≠ | Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615-635. DOI ↗ | Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗ |
| 别名 | Dynamic Fuzzy RDD, DFRD, Time-varying Fuzzy RD, Dynamic Fuzzy RD Design | Panel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDD |
| 相关≠ | 4 | 5 |
| 摘要≠ | Dynamic Fuzzy Regression Discontinuity Design extends the standard fuzzy RDD to a panel or multi-period setting, allowing researchers to estimate how the causal effect of a probabilistic threshold-based treatment evolves over time. By combining an IV-based fuzzy first stage with time-indexed outcomes, it traces treatment effects across multiple post-treatment periods, not just at a single cross-sectional snapshot. | Panel data regression discontinuity design (Panel RDD) combines the sharp local identification of a regression discontinuity with the within-unit variation available in repeated-observation panel data. Units are observed across multiple periods, and treatment is assigned based on whether a running variable crosses a known threshold. By leveraging both the discontinuity and panel structure, researchers can control for unobserved unit-level heterogeneity while estimating a causal treatment effect near the threshold. |
| ScholarGate数据集 ↗ |
|
|