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Fuzzy Regression Discontinuity Design×Lokalni prosečan efekat tretmana (LATE / CACE)×
OblastKauzalno zaključivanjeKauzalno zaključivanje
PorodicaRegression modelRegression model
Godina nastanka20011994
TvoracHahn, Todd & van der KlaauwImbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
TipQuasi-experimental causal inferenceInstrumental-variable causal estimand
Temeljni izvorHahn, 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 ↗Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗
Drugi naziviFuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDDLATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
Srodne55
SažetakFuzzy 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.The Local Average Treatment Effect is an instrumental-variable estimand, introduced by Imbens and Angrist (1994) and formalised with Rubin (1996), that recovers the average treatment effect for the subpopulation of compliers — units whose treatment status is actually moved by the instrument. It is closely tied to compliance analysis.
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ScholarGateUporedite metode: Fuzzy Regression Discontinuity · Local Average Treatment Effect. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare