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Ruimtelijke Fuzzy Regressie Discontinuïteitsontwerp×Fuzzy Regression Discontinuity Design×
VakgebiedCausale inferentieCausale inferentie
FamilieRegression modelRegression model
Jaar van ontstaan20152001
GrondleggerKeele & Titiunik (2015); fuzzy extension of geographic RDD building on Imbens & Lemieux (2008)Hahn, Todd & van der Klaauw
TypeQuasi-experimental causal inference / IV-based spatial designQuasi-experimental causal inference
Oorspronkelijke bronKeele, L., & Titiunik, R. (2015). Geographic Boundaries as Regression Discontinuities. Political Analysis, 23(1), 127-155. 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 ↗
AliassenSpatial Fuzzy RD, Geographic Fuzzy RDD, Spatial Fuzzy RDD, Geo-Fuzzy RDFuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
Verwant55
SamenvattingSpatial Fuzzy Regression Discontinuity Design (Spatial Fuzzy RDD) estimates a local average treatment effect when a geographic boundary determines treatment eligibility but some units on either side of the boundary fail to comply with their assigned status. It combines the spatial running-variable logic of geographic RDD with the instrumental-variable correction for imperfect compliance used in fuzzy RDD.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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ScholarGateMethoden vergelijken: Spatial Fuzzy Regression Discontinuity · Fuzzy Regression Discontinuity. Geraadpleegd op 2026-06-19 via https://scholargate.app/nl/compare