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複数期間ファジー回帰不連続デザイン×Fuzzy Regression Discontinuity Design×
分野因果推論因果推論
系統Regression modelRegression model
提唱年2001 (fuzzy RD); multi-period extension ~2010s2001
提唱者Hahn, Todd & Van der Klaauw (foundational fuzzy RD, 2001); extended to multi-period settings by Cattaneo, Idrobo & Titiunik and subsequent applied literatureHahn, Todd & van der Klaauw
種類Quasi-experimental causal inferenceQuasi-experimental causal inference
原典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 ↗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 ↗
別名multi-period fuzzy RDD, fuzzy RD with repeated assignment, multi-wave fuzzy RD, staggered fuzzy RDDFuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
関連45
概要Multi-period fuzzy regression discontinuity design estimates a local average treatment effect when a cutoff rule only partially determines treatment — that is, crossing the threshold raises the probability of treatment but does not guarantee it — and when this assignment process is observed across two or more time periods or cohorts, enabling pooled or period-specific causal estimates under repeated near-threshold comparisons.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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ScholarGate手法を比較: Multi-period Fuzzy Regression Discontinuity · Fuzzy Regression Discontinuity. 2026-06-19に以下より取得 https://scholargate.app/ja/compare