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| 政策評価における反事実インパクト評価(CIE)× | 反実仮想による影響評価(CIE)× | |
|---|---|---|
| 分野 | 因果推論 | 因果推論 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1974 (Rubin potential outcomes); 2010s (EU policy CIE formalisation) | 1970s–2000s |
| 提唱者≠ | Rubin (potential outcomes framework); European Commission DG Research formalised policy CIE guidelines | Heckman, Imbens, Rubin, and the program evaluation literature |
| 種類≠ | Quasi-experimental causal evaluation | Causal inference / program evaluation |
| 原典≠ | Imbens, G. W., & Rubin, D. B. (2015). Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. Cambridge University Press. ISBN: 978-0521885881 | 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. DOI ↗ |
| 別名 | CIE, policy CIE, counterfactual policy evaluation, impact evaluation | CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation |
| 関連 | 5 | 5 |
| 概要≠ | 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. | 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. |
| ScholarGateデータセット ↗ |
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