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| Regression Discontinuity Design Fuzzy× | Difference-in-Differences (Diff-in-Diff)× | |
|---|---|---|
| Campo≠ | Inferenza causale | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2001 | 1994 |
| Ideatore≠ | Hahn, Todd & van der Klaauw | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Tipo≠ | Quasi-experimental causal inference | Causal inference / panel regression |
| 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 ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Alias≠ | Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| 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. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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