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| Đánh giá Tác động Phản thực tế (CIE)× | Phương pháp Kiểm soát Tổng hợp (SCM)× | |
|---|---|---|
| Lĩnh vực | Suy luận nhân quả | Suy luận nhân quả |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1970s–2000s | 2003–2010 |
| Người khởi xướng≠ | Heckman, Imbens, Rubin, and the program evaluation literature | Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010) |
| Loại≠ | Causal inference / program evaluation | Quasi-experimental causal inference |
| Công trình gốc≠ | 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 ↗ | Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗ |
| Tên gọi khác | CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation | SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method |
| Liên quan≠ | 5 | 4 |
| Tóm tắt≠ | 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. | The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect. |
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