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| 다기간 회귀 불연속 설계× | 회귀 불연속 설계의 패널 데이터 (Panel RDD)× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2010s–2020s | 1960 (original RDD); panel extension codified 2000s–2010s |
| 창시자≠ | Cattaneo, Idrobo & Titiunik (foundations); extended by multiple authors for repeated-period settings | Thistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied work |
| 유형≠ | Quasi-experimental causal inference | Causal inference / quasi-experimental |
| 원전≠ | Cattaneo, M. D., Idrobo, N., & Titiunik, R. (2020). A Practical Introduction to Regression Discontinuity Designs: Foundations. Cambridge University Press. DOI ↗ | Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗ |
| 별칭 | multi-wave RD, repeated RDD, dynamic RD, multi-cutoff RDD | Panel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDD |
| 관련≠ | 3 | 5 |
| 요약≠ | Multi-period Regression Discontinuity Design extends the classic RDD to settings where a cutoff-based treatment is applied in multiple waves, across repeated time periods, or with varying thresholds. By pooling or comparing period-specific discontinuity estimates, researchers gain statistical precision and can examine how causal effects evolve or persist over time. | 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. |
| ScholarGate데이터셋 ↗ |
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