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| 정책 평가 사건 연구 설계× | 합성 통제 방법 (SCM)× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1993-2021 | 2010 |
| 창시자≠ | Andrews (1993), MacKinlay (1997); formalized for policy evaluation by Freyaldenhoven, Hansen & Shapiro (2019) and Callaway & Sant'Anna (2021) | Abadie, Diamond & Hainmueller |
| 유형≠ | Quasi-experimental / causal inference | Counterfactual causal-inference model |
| 원전≠ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. 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 ↗ |
| 별칭 | event study, event-study DiD, dynamic DiD, PEESD | synthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM) |
| 관련 | 5 | 5 |
| 요약≠ | A policy evaluation event study design is a quasi-experimental approach that estimates causal effects of a policy by plotting treatment-period-by-period coefficients around a common event time. It extends difference-in-differences to visualize both pre-treatment parallel trends and the dynamic post-treatment evolution of the policy effect, and has become the standard credibility check in applied policy research. | The Synthetic Control Method, introduced by Abadie, Diamond and Hainmueller in 2010, builds a weighted counterfactual for a single treated unit from a pool of untreated donor units. It is widely regarded as the gold standard for evaluating large policy interventions, natural experiments, and N=1 case studies where no obvious comparison unit exists. |
| ScholarGate데이터셋 ↗ |
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