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이질적 처리 효과 회귀 불연속 설계 (HTE-RDD)×국소 평균 처리 효과 (LATE / CACE)×
분야인과추론인과추론
계열Regression modelRegression model
기원 연도20151994
창시자Dong & Lewbel (2015); Chiang, Hsu & Sasaki (2019)Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
유형Quasi-experimental causal inference with effect heterogeneityInstrumental-variable causal estimand
원전Dong, Y., & Lewbel, A. (2015). Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models. Review of Economics and Statistics, 97(5), 1081-1092. DOI ↗Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗
별칭HTE-RDD, heterogeneous RDD, subgroup RDD, effect heterogeneity RDLATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
관련45
요약Heterogeneous Treatment Effect RDD extends the classic regression discontinuity framework to detect and estimate how the causal effect of crossing an assignment cutoff varies across subgroups or along covariates. Rather than reporting a single local average treatment effect at the threshold, HTE-RDD maps how treatment impact differs by individual characteristics, enabling richer policy conclusions about who benefits most or least from a threshold-based intervention.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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ScholarGate방법 비교: Heterogeneous Treatment Effect Regression Discontinuity Design · Local Average Treatment Effect. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare