השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| הבדלים-בהבדלים (DiD) של אפקט טיפול הטרוגני (HTE-DiD)× | שיטת הבקרה הסינתטית (SCM)× | |
|---|---|---|
| תחום | הסקה סיבתית | הסקה סיבתית |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 2021 | 2003–2010 |
| הוגה השיטה≠ | Callaway & Sant'Anna; Sun & Abraham | Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010) |
| סוג≠ | Causal inference / panel regression | Quasi-experimental causal inference |
| מקור מכונן≠ | 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 ↗ |
| כינויים | HTE-DiD, heterogeneous DiD, CATT estimator, group-time ATT | SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method |
| קשורות | 4 | 4 |
| תקציר≠ | HTE-DiD extends the classic Difference-in-Differences estimator to settings where treatment effects vary across units, time periods, or treatment cohorts. Developed formally by Callaway and Sant'Anna (2021) and Sun and Abraham (2021), it avoids the biases that arise when a conventional two-way fixed-effects regression is used with staggered adoption or effect heterogeneity, by estimating cohort-and-time-specific average treatment effects that can then be aggregated flexibly. | 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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