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| 회귀 불연속 설계의 패널 데이터 (Panel RDD)× | 퍼지 회귀 불연속 설계× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1960 (original RDD); panel extension codified 2000s–2010s | 2001 |
| 창시자≠ | Thistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied work | Hahn, Todd & van der Klaauw |
| 유형≠ | Causal inference / quasi-experimental | Quasi-experimental causal inference |
| 원전≠ | Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗ | 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 ↗ |
| 별칭 | Panel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDD | Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD |
| 관련 | 5 | 5 |
| 요약≠ | 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. | Fuzzy Regression Discontinuity Design (Fuzzy RDD) estimates causal effects when eligibility for a treatment is determined by a threshold on a running variable but actual take-up of that treatment is imperfect — some eligible units do not receive treatment and some ineligible units do. The cutoff acts as an instrument, and the estimand is a Local Average Treatment Effect (LATE) for compliers near the threshold. |
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