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| 패널 데이터 퍼지 회귀 불연속 설계× | 퍼지 회귀 불연속 설계× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2001 (fuzzy RDD); panel extension circa 2011 | 2001 |
| 창시자≠ | Hahn, Todd & Van der Klaauw; extended to panel settings by Papay, Willett & Murnane and others | Hahn, Todd & van der Klaauw |
| 유형 | Quasi-experimental causal inference | Quasi-experimental causal inference |
| 원전 | 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 ↗ | 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 Fuzzy RDD, Panel FRD, Fuzzy RD with Panel Data, Panel Fuzzy RD | Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD |
| 관련 | 5 | 5 |
| 요약≠ | 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. | 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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