方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 面板数据匹配估计量× | 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≠ | 1997-2021 | 1985–2004 |
| 提出者≠ | Heckman, Ichimura & Todd (1997); Imai, Kim & Wang (2021) for panel extension | Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004) |
| 类型≠ | Quasi-experimental causal estimator | Causal inference / panel regression |
| 开创性文献≠ | Heckman, J. J., Ichimura, H., & Todd, P. E. (1997). Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme. Review of Economic Studies, 64(4), 605-654. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 别名 | panel matching, matching-on-panel-data, longitudinal matching estimator, PDME | Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff |
| 相关≠ | 6 | 4 |
| 摘要≠ | The panel data matching estimator identifies causal treatment effects by pairing each treated unit with one or more control units that share similar covariate histories in the pre-treatment periods. By exploiting the longitudinal structure of panel data, it controls for both observed time-varying confounders and stable unit characteristics, estimating the average treatment effect on the treated (ATT) without requiring a parallel-trends assumption. | 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 ↗ |
|
|