Confronta i metodi

	Valutazione d'Impatto Controfattuale (CIE) per la Valutazione delle Politiche	Metodo delle Variabili Strumentali (IV) per l'Inferenza Causale
Campo	Inferenza causale	Economia sanitaria
Famiglia	Regression model	Process / pipeline
Anno di origine	1974 (Rubin potential outcomes); 2010s (EU policy CIE formalisation)	1990s (modern applications)
Ideatore	Rubin (potential outcomes framework); European Commission DG Research formalised policy CIE guidelines	Angrist & Pischke (applied econometrics); rooted in econometric theory
Tipo	Quasi-experimental causal evaluation	Method
Fonte seminale	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.
Alias	CIE, policy CIE, counterfactual policy evaluation, impact evaluation	IV, two-stage least squares, TSLS, causal estimation
Correlati	5	3
Sintesi	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.