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Fuzzy regresjonsdiskontinuitetsdesign for politikkutvärdering×Fuzzy Regression Discontinuity Design×
FagfeltKausal inferensKausal inferens
FamilieRegression modelRegression model
Opprinnelsesår20012001
OpphavspersonHahn, Todd & Van der KlaauwHahn, Todd & van der Klaauw
TypeQuasi-experimental / local IV estimatorQuasi-experimental causal inference
Opprinnelig kildeHahn, 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 ↗
AliasFuzzy RDD, Fuzzy RD, Fuzzy Regression Discontinuity, Imperfect Compliance RDDFuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
Relaterte55
SammendragFuzzy 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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ScholarGateSammenlign metoder: Policy Evaluation Fuzzy Regression Discontinuity · Fuzzy Regression Discontinuity. Hentet 2026-06-19 fra https://scholargate.app/no/compare