Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Différences-en-différences robustes× | Différence-en-différences multi-périodes (DiD échelonné)× | |
|---|---|---|
| Domaine | Inférence causale | Inférence causale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2021-2023 | 2021 |
| Auteur d'origine≠ | Callaway & Sant'Anna; Sun & Abraham; Roth et al. (synthesised 2021-2023) | Callaway & Sant'Anna; Goodman-Bacon |
| Type | Causal inference / panel regression | Causal inference / panel regression |
| Source fondatrice | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ |
| Alias | robust DiD, heterogeneity-robust DiD, staggered DiD, disaggregated ATT DiD | staggered DiD, multi-period DiD, staggered difference-in-differences, heterogeneous timing DiD |
| Apparentées | 5 | 5 |
| Résumé≠ | Robust Difference-in-Differences is a family of modern DiD estimators designed to remain valid when treatment timing is staggered across units and treatment effects are heterogeneous over time or across groups. Classical two-way fixed-effects (TWFE) DiD can be severely biased in such settings; robust variants estimate group-time average treatment effects (ATTs) separately and then aggregate them in a theoretically sound way. | Multi-period Difference-in-Differences extends the classic two-period DiD framework to settings where units adopt treatment at different points in time. Formalised by Callaway and Sant'Anna (2021) and Goodman-Bacon (2021), it decomposes the overall treatment effect into group-time average treatment effects and addresses the bias that arises when conventional two-way fixed-effects regressions are applied to staggered adoption designs. |
| ScholarGateJeu de données ↗ |
|
|