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| 多期匹配估计量× | 面板数据匹配估计量× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2005 | 1997-2021 |
| 提出者≠ | Abadie (2005); Imbens & Wooldridge (2009) | Heckman, Ichimura & Todd (1997); Imai, Kim & Wang (2021) for panel extension |
| 类型≠ | Quasi-experimental / causal inference | Quasi-experimental causal estimator |
| 开创性文献≠ | Abadie, A. (2005). Semiparametric Difference-in-Differences Estimators. Review of Economic Studies, 72(1), 1-19. DOI ↗ | 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 ↗ |
| 别名 | panel matching estimator, longitudinal matching, multi-wave matching, repeated-cross-section matching | panel matching, matching-on-panel-data, longitudinal matching estimator, PDME |
| 相关 | 6 | 6 |
| 摘要≠ | The multi-period matching estimator extends the standard matching framework to settings with multiple time periods, pairing each treated unit to similar untreated units based on pre-treatment covariates or propensity scores, then using within-pair before-after differences to estimate the average treatment effect on the treated (ATT). Leveraging repeated observations, it simultaneously controls for observed confounders and time-invariant unobserved heterogeneity. | 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. |
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