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| Différences-en-Différences Échelonnées× | Méthode du Contrôle Synthétique (SCM)× | |
|---|---|---|
| Domaine | Inférence causale | Inférence causale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2021 | 2010 |
| Auteur d'origine≠ | Callaway & Sant'Anna; Sun & Abraham | Abadie, Diamond & Hainmueller |
| Type≠ | Quasi-experimental panel causal estimator | Counterfactual causal-inference model |
| 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 ↗ | Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗ |
| Alias≠ | staggered DID, staggered adoption DID, heterogeneous treatment DID, Callaway-Sant'Anna estimator | synthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM) |
| Apparentées≠ | 4 | 5 |
| Résumé≠ | 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. | The Synthetic Control Method, introduced by Abadie, Diamond and Hainmueller in 2010, builds a weighted counterfactual for a single treated unit from a pool of untreated donor units. It is widely regarded as the gold standard for evaluating large policy interventions, natural experiments, and N=1 case studies where no obvious comparison unit exists. |
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