השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| שיטת הבקרה הסינתטית הדינמית× | הפרש-הפרשים דינמי× | |
|---|---|---|
| תחום | הסקה סיבתית | הסקה סיבתית |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 2010 | 2021 |
| הוגה השיטה≠ | Abadie, Diamond & Hainmueller (2010); dynamic extensions by Abadie (2021) and others | Callaway & Sant'Anna; Sun & Abraham |
| סוג≠ | Comparative case study / counterfactual estimation | Causal inference / quasi-experimental |
| מקור מכונן≠ | 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 ↗ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ |
| כינויים | Dynamic SCM, Time-varying synthetic control, Multi-period synthetic control, DSC | Dynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD |
| קשורות≠ | 5 | 4 |
| תקציר≠ | The Dynamic Synthetic Control Method extends the classic synthetic control framework to evaluate treatments that unfold over multiple periods or change in intensity over time. It constructs a weighted combination of untreated units that matches the treated unit in pre-treatment outcomes, then traces the full time path of treatment effects period by period after the intervention — capturing not just an average effect but how the effect evolves dynamically. | 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. |
| ScholarGateמערך נתונים ↗ |
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