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| Αξιολόγηση Πολιτικής με Αντιστοίχιση Βαθμολογίας Προδιάθεσης× | Αδρή Ακριβής Αντιστοίχιση (CEM)× | |
|---|---|---|
| Πεδίο | Αιτιακή Συμπερασματολογία | Αιτιακή Συμπερασματολογία |
| Οικογένεια | Regression model | Regression model |
| Έτος προέλευσης≠ | 1983; policy evaluation adaptation 1997 | 2011-2012 |
| Δημιουργός≠ | Rosenbaum & Rubin (1983); Heckman, Ichimura & Todd (1997) for program/policy evaluation application | Iacus, King, & Porro |
| Τύπος≠ | Quasi-experimental matching estimator | Matching / causal inference |
| Θεμελιώδης πηγή≠ | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55. DOI ↗ | Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗ |
| Εναλλακτικές ονομασίες≠ | PSM policy evaluation, policy PSM, propensity matching for program evaluation, PSM treatment evaluation | CEM, coarsened matching, monotonic imbalance bounding matching |
| Συναφείς | 6 | 6 |
| Σύνοψη≠ | Policy evaluation propensity score matching applies the propensity score framework — originally developed by Rosenbaum and Rubin (1983) and operationalized for program evaluation by Heckman et al. (1997) — to estimate the causal effect of a policy intervention. It constructs a credible comparison group from non-participants by matching them to participants on their estimated probability of receiving the treatment, enabling unbiased effect estimation without random assignment. | 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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