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Fuzzy Regression Discontinuity×Metoda różnic w różnicach (Diff-in-Diff)×
DziedzinaWnioskowanie przyczynoweEkonometria
RodzinaRegression modelRegression model
Rok powstania20011994
TwórcaHahn, Todd & van der KlaauwCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypQuasi-experimental causal inferenceCausal inference / panel regression
Źródło pierwotneHahn, 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
Inne nazwyFuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDDdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Pokrewne55
PodsumowanieFuzzy 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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  3. PUBLISHED

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ScholarGatePorównaj metody: Fuzzy Regression Discontinuity · Difference-in-Differences. Pobrano 2026-06-15 z https://scholargate.app/pl/compare