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。
| 模糊断点回归政策评估 (Fuzzy Regression Discontinuity for Policy Evaluation)× | 政策评估断点回归设计× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2001 | 1960; policy evaluation applications widespread from 2000s |
| 提出者≠ | Hahn, Todd & Van der Klaauw | Thistlethwaite & Campbell (1960); popularized in policy evaluation by Lee & Lemieux (2010) |
| 类型≠ | Quasi-experimental / local IV estimator | Quasi-experimental causal design |
| 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 ↗ | Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗ |
| 别名 | Fuzzy RDD, Fuzzy RD, Fuzzy Regression Discontinuity, Imperfect Compliance RDD | Policy RDD, RD design in policy evaluation, regression discontinuity policy analysis, RDD policy impact |
| 相关 | 5 | 5 |
| 摘要≠ | Fuzzy Regression Discontinuity Design (Fuzzy RDD) estimates the causal effect of a policy when eligibility is determined by crossing a threshold on a continuous score, but actual take-up or compliance is imperfect. Developed formally by Hahn, Todd, and Van der Klaauw (2001), it uses the threshold as an instrumental variable to recover a Local Average Treatment Effect (LATE) among compliers near the cutoff. | Policy Evaluation Regression Discontinuity Design (Policy RDD) exploits a known eligibility threshold in a policy rule to estimate the causal effect of that policy on outcomes. Units just below the cutoff serve as a credible comparison group for units just above it, making RDD one of the most transparent quasi-experimental strategies for assessing what a policy actually achieves. |
| ScholarGate数据集 ↗ |
|
|