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Fuzzy Regression Discontinuity in Education Research×Metoda różnic w różnicach (Diff-in-Diff)×
DziedzinaWnioskowanie przyczynoweEkonometria
RodzinaRegression modelRegression model
Rok powstaniaLate 1990s–2000s1994
TwórcaImbens & Lemieux (2008); applied in education by Jacob & Lefgren (2004) and Angrist & Lavy (1999)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypQuasi-experimental / causal inferenceCausal inference / panel regression
Źródło pierwotneImbens, 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
Inne nazwyFuzzy RDD, Fuzzy RD, Imperfect RDD, Non-sharp RDdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Pokrewne45
PodsumowanieFuzzy Regression Discontinuity Design (Fuzzy RDD) is a quasi-experimental causal method that exploits a known score threshold — such as a test cutoff — to estimate the effect of a program or intervention when assignment is imperfect. Widely used in education research to evaluate summer school, remedial programs, scholarships, and class-size rules, it uses two-stage least squares to recover a local average treatment effect for students 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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ScholarGatePorównaj metody: Fuzzy Regression Discontinuity in Education Research · Difference-in-Differences. Pobrano 2026-06-18 z https://scholargate.app/pl/compare