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| Policy Evaluation Counterfactual Impact Evaluation (CIE)× | Instrumentvariabelmetoden (IV) för kausal inferens× | |
|---|---|---|
| Ämnesområde≠ | Kausal inferens | Hälsoekonomi |
| Familj≠ | Regression model | Process / pipeline |
| Ursprungsår≠ | 1974 (Rubin potential outcomes); 2010s (EU policy CIE formalisation) | 1990s (modern applications) |
| Upphovsperson≠ | Rubin (potential outcomes framework); European Commission DG Research formalised policy CIE guidelines | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| Typ≠ | Quasi-experimental causal evaluation | Method |
| Ursprungskälla≠ | 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. link ↗ |
| Alias | CIE, policy CIE, counterfactual policy evaluation, impact evaluation | IV, two-stage least squares, TSLS, causal estimation |
| Närliggande≠ | 5 | 3 |
| Sammanfattning≠ | 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. |
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