手法を比較

	回帰キンクデザイン (RKD)	因果推論のための操作変数（IV）法
分野	因果推論	医療経済学
系統	Regression model	Process / pipeline
提唱年	2015	1990s (modern applications)
提唱者	Card, Lee, Pei & Weber	Angrist & Pischke (applied econometrics); rooted in econometric theory
種類	Quasi-experimental design (slope-based RDD)	Method
原典	Card, D., Lee, D. S., Pei, Z. & Weber, A. (2015). Inference on Causal Effects in a Generalized Regression Kink Design. Econometrica, 83(6), 2453-2483.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
別名	RKD, regression kink design, kink regression discontinuity, Regresyon Kırılma Tasarımı (RKD — Regression Kink Design)	IV, two-stage least squares, TSLS, causal estimation
関連	4	3
概要	The Regression Kink Design is a quasi-experimental method that estimates a causal effect when a policy rule creates a change in slope (a kink) — rather than a jump — at a known threshold of a running variable. It was formalised as a generalized design by Card, Lee, Pei and Weber (2015) and is the slope-based counterpart of the regression discontinuity design.	Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes.