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Designul de discontinuitate a regresiei (RDD)×Two-Stage Least Squares (2SLS)×
DomeniuInferență cauzalăInferență cauzală
FamilieRegression modelRegression model
Anul apariției20082009
Autorul originalImbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)
TipQuasi-experimental causal designInstrumental-variables regression
Sursa seminalăImbens, 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
Denumiri alternativeRDD, regression discontinuity design, sharp RDD, fuzzy RDDinstrumental variables, IV estimation, 2SLS, instrumental variable regression
Înrudite55
RezumatRegression 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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ScholarGateCompară metode: Regression Discontinuity · Two-Stage Least Squares (2SLS). Preluat la 2026-06-18 de pe https://scholargate.app/ro/compare