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| Regression Discontinuity Design Fuzzy× | Effetto Medio Locale del Trattamento (LATE / CACE)× | |
|---|---|---|
| Campo | Inferenza causale | Inferenza causale |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2001 | 1994 |
| Ideatore≠ | Hahn, Todd & van der Klaauw | Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996) |
| Tipo≠ | Quasi-experimental causal inference | Instrumental-variable causal estimand |
| Fonte seminale≠ | 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 ↗ | Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗ |
| Alias | Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD | LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE) |
| Correlati | 5 | 5 |
| Sintesi≠ | 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. | The Local Average Treatment Effect is an instrumental-variable estimand, introduced by Imbens and Angrist (1994) and formalised with Rubin (1996), that recovers the average treatment effect for the subpopulation of compliers — units whose treatment status is actually moved by the instrument. It is closely tied to compliance analysis. |
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