手法を比較

	反実仮想による影響評価（CIE）	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	1970s–2000s	1990s (modern applications)
提唱者	Heckman, Imbens, Rubin, and the program evaluation literature	Angrist & Pischke (applied econometrics); rooted in econometric theory
種類	Causal inference / program evaluation	Method
原典	Heckman, J. J., & Vytlacil, E. J. (2007). Econometric evaluation of social programs, Part I: Causal models, structural models and econometric policy evaluation. Handbook of Econometrics, 6B, 4779-4874.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
別名	CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation	IV, two-stage least squares, TSLS, causal estimation
関連	5	3
概要	Counterfactual Impact Evaluation is a family of causal methods that estimates the effect of an intervention by comparing what actually happened to participants with what would have happened had the intervention not taken place. Formalised in the Rubin Causal Model and extended by Heckman, Imbens and others, CIE underlies most modern program and policy evaluation practice.	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.