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| Multiperioden-Matching-Schätzer× | Coarsened Exact Matching (CEM)× | |
|---|---|---|
| Fachgebiet | Kausale Inferenz | Kausale Inferenz |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2005 | 2011-2012 |
| Urheber≠ | Abadie (2005); Imbens & Wooldridge (2009) | Iacus, King, & Porro |
| Typ≠ | Quasi-experimental / causal inference | Matching / causal inference |
| Wegweisende Quelle≠ | Abadie, A. (2005). Semiparametric Difference-in-Differences Estimators. Review of Economic Studies, 72(1), 1-19. DOI ↗ | Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗ |
| Aliasnamen≠ | panel matching estimator, longitudinal matching, multi-wave matching, repeated-cross-section matching | CEM, coarsened matching, monotonic imbalance bounding matching |
| Verwandt | 6 | 6 |
| Zusammenfassung≠ | 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. |
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