方法对比
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| 面板数据模糊回归不连续设计× | 面板数据工具变量 (Panel IV / 2SLS)× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2001 (fuzzy RDD); panel extension circa 2011 | 1978-1991 |
| 提出者≠ | Hahn, Todd & Van der Klaauw; extended to panel settings by Papay, Willett & Murnane and others | Hausman (1978); Anderson & Hsiao (1982); Arellano & Bond (1991) |
| 类型≠ | Quasi-experimental causal inference | Causal inference / panel regression |
| 开创性文献≠ | Hahn, J., Todd, P., & Van der Klaauw, W. (2001). Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design. Review of Economic Studies, 68(1), 201-209. DOI ↗ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277-297. DOI ↗ |
| 别名 | Panel Fuzzy RDD, Panel FRD, Fuzzy RD with Panel Data, Panel Fuzzy RD | Panel IV, Panel 2SLS, Within-IV, Fixed-Effects IV |
| 相关≠ | 5 | 4 |
| 摘要≠ | Panel Data Fuzzy Regression Discontinuity Design (Panel FRD) extends the fuzzy RDD framework to settings where multiple observations per unit are available over time. It exploits a probabilistic — rather than deterministic — threshold-crossing rule to identify a local average treatment effect (LATE) while controlling for unit-level and time-level fixed effects, sharpening identification in repeated-measures contexts. | Panel data instrumental variables combines the bias-correcting power of instrumental variables (IV) with the within-unit variation exploited by panel data methods. It addresses endogeneity — omitted variables, reverse causation, or measurement error — in longitudinal settings where observations are repeated across units and time. Seminal contributions come from Hausman (1978) on specification testing and Arellano and Bond (1991) on GMM-based panel IV. |
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