方法对比
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| 动态双重差分× | 面板数据双重差分法 (Panel DiD / TWFE)× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2021 | 1985–2004 |
| 提出者≠ | Callaway & Sant'Anna; Sun & Abraham | Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004) |
| 类型≠ | Causal inference / quasi-experimental | Causal inference / panel regression |
| 开创性文献≠ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 别名 | Dynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD | Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff |
| 相关 | 4 | 4 |
| 摘要≠ | 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. | Panel Data Difference-in-Differences extends the classic two-period DiD design to settings with multiple units observed across many time periods. By absorbing unit-level fixed effects and time fixed effects simultaneously, it isolates the causal effect of a treatment or policy change while controlling for both time-invariant unit heterogeneity and common time shocks affecting all units. |
| ScholarGate数据集 ↗ |
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