Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Багатоперіодний різницевий метод (Staggered Difference-in-Differences)× | Регресійний розривний дизайн (RDD)× | |
|---|---|---|
| Галузь | Причинно-наслідковий висновок | Причинно-наслідковий висновок |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2021 | 2008 |
| Автор методу≠ | Callaway & Sant'Anna; Sun & Abraham | Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction) |
| Тип≠ | Quasi-experimental panel causal estimator | Quasi-experimental causal design |
| Основоположне джерело≠ | Callaway, B. & Sant'Anna, P. H. C. (2021). Difference-in-Differences with Multiple Time Periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ | Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗ |
| Інші назви≠ | staggered DID, staggered adoption DID, heterogeneous treatment DID, Callaway-Sant'Anna estimator | RDD, regression discontinuity design, sharp RDD, fuzzy RDD |
| Пов'язані≠ | 4 | 5 |
| Підсумок≠ | Staggered Difference-in-Differences is a generalisation of DID for panel designs in which treatment is rolled out to different groups at different times. Introduced in the modern form by Callaway and Sant'Anna (2021) and Sun and Abraham (2021), it corrects the bias that classical two-way fixed-effects (TWFE) estimators suffer when treatment effects are heterogeneous across cohorts and over time. | Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold. |
| ScholarGateНабір даних ↗ |
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