方法对比

	面板数据匹配估计量	粗化精确匹配 (CEM)
领域	因果推断	因果推断
方法族	Regression model	Regression model
起源年份	1997-2021	2011-2012
提出者	Heckman, Ichimura & Todd (1997); Imai, Kim & Wang (2021) for panel extension	Iacus, King, & Porro
类型	Quasi-experimental causal estimator	Matching / causal inference
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.	Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24.
别名	panel matching, matching-on-panel-data, longitudinal matching estimator, PDME	CEM, coarsened matching, monotonic imbalance bounding matching
相关	6	6
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.	Coarsened Exact Matching is a preprocessing method that achieves covariate balance by temporarily coarsening continuous variables into bins, exactly matching treated and control units within those bins, and then discarding all unmatched units. Introduced by Iacus, King, and Porro (2011, 2012), it bounds imbalance on each covariate independently, yielding a matched sample on which any estimator can be applied without relying on a propensity score model.