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| Dynamische Differenz-von-Differenzen× | Synthetische Kontrollmethode (SCM)× | |
|---|---|---|
| Fachgebiet | Kausale Inferenz | Kausale Inferenz |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2021 | 2003–2010 |
| Urheber≠ | Callaway & Sant'Anna; Sun & Abraham | Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010) |
| Typ≠ | Causal inference / quasi-experimental | Quasi-experimental causal inference |
| Wegweisende Quelle≠ | 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 ↗ |
| Aliasnamen | Dynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD | SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method |
| Verwandt | 4 | 4 |
| Zusammenfassung≠ | Dynamic Difference-in-Differences extends the classic DiD framework to settings where units adopt treatment at different times. Rather than collapsing all variation into a single 2x2 comparison, it estimates group-time average treatment effects for each adoption cohort at each calendar period, then aggregates them into interpretable summaries of the causal effect over event time. | The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect. |
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