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| 정책 평가 차이-이중차분× | 합성 통제 방법 (SCM)× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1978-2009 | 2003–2010 |
| 창시자≠ | Ashenfelter (1978); Heckman, LaLonde & Smith (1999); Imbens & Wooldridge (2009) | Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010) |
| 유형≠ | Quasi-experimental / policy evaluation | Quasi-experimental causal inference |
| 원전≠ | Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, 47(1), 5-86. 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 | policy DiD, program evaluation DiD, policy impact DiD, DiD policy assessment | SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method |
| 관련 | 4 | 4 |
| 요약≠ | Policy Evaluation DiD applies the difference-in-differences estimator specifically to assess the causal impact of government programs, regulations, or policy reforms. It compares outcome changes in a group exposed to the policy against a comparable untreated group, before and after the policy took effect, isolating the net policy effect from pre-existing trends and time-common shocks. | 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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