Módszerek összehasonlítása

	Multi-period Matching Estimator	Coarsened Exact Matching (CEM)
Tudományterület	Oksági következtetés	Oksági következtetés
Módszercsalád	Regression model	Regression model
Keletkezés éve	2005	2011-2012
Megalkotó	Abadie (2005); Imbens & Wooldridge (2009)	Iacus, King, & Porro
Típus	Quasi-experimental / causal inference	Matching / causal inference
Alapmű	Abadie, A. (2005). Semiparametric Difference-in-Differences Estimators. Review of Economic Studies, 72(1), 1-19.	Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24.
Alternatív nevek	panel matching estimator, longitudinal matching, multi-wave matching, repeated-cross-section matching	CEM, coarsened matching, monotonic imbalance bounding matching
Kapcsolódó	6	6
Összefoglaló	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.	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.