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| Disegno a Regressione Discontinua (RDD)× | Variabili Strumentali tramite Minimi Quadrati a Due Stadi (IV/2SLS)× | |
|---|---|---|
| Campo | Inferenza causale | Inferenza causale |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2008 | 2009 |
| Ideatore≠ | Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction) | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| Tipo≠ | Quasi-experimental causal design | Instrumental-variables regression |
| Fonte seminale≠ | Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Alias | RDD, regression discontinuity design, sharp RDD, fuzzy RDD | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| Correlati | 5 | 5 |
| Sintesi≠ | Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold. | IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009). |
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