방법 비교

	정책 평가 준거영향평가 (CIE)	인과 추론을 위한 도구 변수(IV) 방법
분야	인과추론	보건경제학
계열	Regression model	Process / pipeline
기원 연도	1974 (Rubin potential outcomes); 2010s (EU policy CIE formalisation)	1990s (modern applications)
창시자	Rubin (potential outcomes framework); European Commission DG Research formalised policy CIE guidelines	Angrist & Pischke (applied econometrics); rooted in econometric theory
유형	Quasi-experimental causal evaluation	Method
원전	Imbens, G. W., & Rubin, D. B. (2015). Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. Cambridge University Press. ISBN: 978-0521885881	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
별칭	CIE, policy CIE, counterfactual policy evaluation, impact evaluation	IV, two-stage least squares, TSLS, causal estimation
관련	5	3
요약	Counterfactual Impact Evaluation (CIE) for policy assessment estimates the causal effect of a public policy or programme by comparing observed outcomes of participants against a rigorously constructed counterfactual — what would have happened had the policy not existed. Rooted in the Rubin potential-outcomes framework, CIE is the standard methodology endorsed by the European Commission for evaluating research, innovation, and structural funding programmes.	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.