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Rozmyta regresja skokowa w ocenie polityki×Fuzzy Regression Discontinuity×
DziedzinaWnioskowanie przyczynoweWnioskowanie przyczynowe
RodzinaRegression modelRegression model
Rok powstania20012001
TwórcaHahn, Todd & Van der KlaauwHahn, Todd & van der Klaauw
TypQuasi-experimental / local IV estimatorQuasi-experimental causal inference
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 ↗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 ↗
Inne nazwyFuzzy RDD, Fuzzy RD, Fuzzy Regression Discontinuity, Imperfect Compliance RDDFuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
Pokrewne55
PodsumowanieFuzzy Regression Discontinuity Design (Fuzzy RDD) estimates the causal effect of a policy when eligibility is determined by crossing a threshold on a continuous score, but actual take-up or compliance is imperfect. Developed formally by Hahn, Todd, and Van der Klaauw (2001), it uses the threshold as an instrumental variable to recover a Local Average Treatment Effect (LATE) among compliers near the cutoff.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.
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ScholarGatePorównaj metody: Policy Evaluation Fuzzy Regression Discontinuity · Fuzzy Regression Discontinuity. Pobrano 2026-06-19 z https://scholargate.app/pl/compare