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| Regression Discontinuity in Sentencing× | 回归断点设计 (Regression Discontinuity Design, RDD)× | |
|---|---|---|
| 领域≠ | Criminology | 因果推断 |
| 方法族≠ | Process / pipeline | Regression model |
| 起源年份≠ | 1983 | 2008 |
| 提出者≠ | Richard A. Berk & David Rauma (criminological application); Donald L. Thistlethwaite & Donald T. Campbell (design origin) | Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction) |
| 类型≠ | Quasi-experimental causal design at a policy threshold | Quasi-experimental causal design |
| 开创性文献≠ | Berk, R. A., & Rauma, D. (1983). Capitalizing on nonrandom assignment to treatments: A regression-discontinuity evaluation of a crime-control program. Journal of the American Statistical Association, 78(381), 21–27. DOI ↗ | Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗ |
| 别名≠ | Sentencing Threshold RDD, Cutoff-Based Justice Evaluation, Risk-Score Discontinuity Design, Age-of-Majority Discontinuity | RDD, regression discontinuity design, sharp RDD, fuzzy RDD |
| 相关≠ | 4 | 5 |
| 摘要≠ | Regression discontinuity (RD) in sentencing exploits the sharp thresholds built into justice policy — sentencing-guideline cutoffs, the age of majority, risk-score thresholds that trigger detention or diversion — to estimate causal effects without a randomized trial. Units just above the cutoff receive a different treatment from units just below it, yet they are otherwise nearly identical, so comparing their outcomes isolates the effect of crossing the line. Berk and Rauma's 1983 evaluation of a crime-control program showed how criminologists can 'capitalize on nonrandom assignment' created by such rules. | Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold. |
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