قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| مُقدّر الفروق في الفروق لتأثيرات المعالجة غير المتجانسة (HTE-DiD)× | بيانات البانل (Panel Data) فرق الفروقات (Difference-in-Differences - DiD)× | |
|---|---|---|
| المجال | الاستدلال السببي | الاستدلال السببي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 2021 | 1985–2004 |
| صاحب الطريقة≠ | Callaway & Sant'Anna; Sun & Abraham | Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004) |
| النوع | Causal inference / panel regression | Causal inference / panel regression |
| المصدر التأسيسي≠ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| الأسماء البديلة | HTE-DiD, heterogeneous DiD, CATT estimator, group-time ATT | Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff |
| ذات صلة | 4 | 4 |
| الملخص≠ | 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. | Panel Data Difference-in-Differences extends the classic two-period DiD design to settings with multiple units observed across many time periods. By absorbing unit-level fixed effects and time fixed effects simultaneously, it isolates the causal effect of a treatment or policy change while controlling for both time-invariant unit heterogeneity and common time shocks affecting all units. |
| ScholarGateمجموعة البيانات ↗ |
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