Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Coarsened Exact Matching (CEM)× | Rozdíl v rozdílech (Diff-in-Diff)× | |
|---|---|---|
| Obor≠ | Kauzální inference | Ekonometrie |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 2011-2012 | 1994 |
| Tvůrce≠ | Iacus, King, & Porro | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Typ≠ | Matching / causal inference | Causal inference / panel regression |
| Původní zdroj≠ | Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Další názvy | CEM, coarsened matching, monotonic imbalance bounding matching | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Příbuzné≠ | 6 | 5 |
| Shrnutí≠ | 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. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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