Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Укрупненное точное сопоставление (CEM)× | Разность разностей (Difference-in-Differences, DiD)× | |
|---|---|---|
| Область≠ | Причинно-следственный вывод | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2011-2012 | 1994 |
| Автор метода≠ | Iacus, King, & Porro | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Тип≠ | Matching / causal inference | Causal inference / panel regression |
| Основополагающий источник≠ | 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 |
| Другие названия | CEM, coarsened matching, monotonic imbalance bounding matching | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Связанные≠ | 6 | 5 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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