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| Prostorni dizajn diskontinuiteta regresije (Spatial RDD)× | Fuzzy regresijski diskontinuitetni dizajn× | |
|---|---|---|
| Područje | Uzročno zaključivanje | Uzročno zaključivanje |
| Obitelj | Regression model | Regression model |
| Godina nastanka≠ | 2010s | 2001 |
| Tvorac≠ | Popularized by Dell (2010); formalized for geographic boundaries by Keele & Titiunik (2015) | Hahn, Todd & van der Klaauw |
| Vrsta | Quasi-experimental causal inference | Quasi-experimental causal inference |
| Temeljni izvor≠ | Dell, M. (2010). The Persistent Effects of Peru's Mining Mita. Econometrica, 78(6), 1863-1903. 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 ↗ |
| Drugi nazivi | Spatial RDD, Geographic RDD, Border RD Design, Geographic Discontinuity Design | Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD |
| Srodne≠ | 4 | 5 |
| Sažetak≠ | Spatial Regression Discontinuity Design uses a geographic or administrative boundary as the threshold that assigns units to treatment. Observations just inside one side of the boundary are compared with those just outside it, exploiting the near-random variation in treatment status near the cutoff to recover a local causal effect. The approach is widely used in economics, political science, and public health when policies or institutions change sharply at a border. | 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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