方法对比

	异质性处理效应回归断点设计（HTE-RDD）	局部平均处理效应（LATE / CACE）
领域	因果推断	因果推断
方法族	Regression model	Regression model
起源年份	2015	1994
提出者	Dong & Lewbel (2015); Chiang, Hsu & Sasaki (2019)	Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
类型	Quasi-experimental causal inference with effect heterogeneity	Instrumental-variable causal estimand
开创性文献	Dong, 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.	Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475.
别名	HTE-RDD, heterogeneous RDD, subgroup RDD, effect heterogeneity RD	LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
相关	4	5
摘要	Heterogeneous 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.