方法对比

	政策评估反事实影响评估 (CIE)	因果推断的工具变量（IV）方法
领域	因果推断	卫生经济学
方法族	Regression model	Process / pipeline
起源年份	1974 (Rubin potential outcomes); 2010s (EU policy CIE formalisation)	1990s (modern applications)
提出者	Rubin (potential outcomes framework); European Commission DG Research formalised policy CIE guidelines	Angrist & Pischke (applied econometrics); rooted in econometric theory
类型	Quasi-experimental causal evaluation	Method
开创性文献	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.
别名	CIE, policy CIE, counterfactual policy evaluation, impact evaluation	IV, two-stage least squares, TSLS, causal estimation
相关	5	3
摘要	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.