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| 정책 평가 차이-이중차분× | 동적 이중차분법 (Dynamic Difference-in-Differences)× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1978-2009 | 2021 |
| 창시자≠ | Ashenfelter (1978); Heckman, LaLonde & Smith (1999); Imbens & Wooldridge (2009) | Callaway & Sant'Anna; Sun & Abraham |
| 유형≠ | Quasi-experimental / policy evaluation | Causal inference / quasi-experimental |
| 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 ↗ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ |
| 별칭 | policy DiD, program evaluation DiD, policy impact DiD, DiD policy assessment | Dynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD |
| 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. | Dynamic Difference-in-Differences extends the classic DiD framework to settings where units adopt treatment at different times. Rather than collapsing all variation into a single 2x2 comparison, it estimates group-time average treatment effects for each adoption cohort at each calendar period, then aggregates them into interpretable summaries of the causal effect over event time. |
| ScholarGate데이터셋 ↗ |
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