Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Динамическое исследование событий на панельных данных× | Динамический метод разностей-разностей× | |
|---|---|---|
| Область | Причинно-следственный вывод | Причинно-следственный вывод |
| Семейство | Regression model | Regression model |
| Год появления | 2021 | 2021 |
| Автор метода≠ | Sun & Abraham (2021); Callaway & Sant'Anna (2021) | Callaway & Sant'Anna; Sun & Abraham |
| Тип≠ | Quasi-experimental / causal inference | Causal inference / quasi-experimental |
| Основополагающий источник | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ |
| Другие названия | dynamic event study, panel event-study regression, leads-and-lags event study, event-time panel design | Dynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD |
| Связанные | 4 | 4 |
| Сводка≠ | The dynamic panel event study is a quasi-experimental method that uses panel data to trace out how a treatment effect evolves over time — before and after a defining event — by estimating a flexible regression of leads and lags around the treatment date. It simultaneously tests for pre-existing parallel trends and maps the full dynamic profile of causal impact across multiple post-event periods. | 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. |
| ScholarGateНабор данных ↗ |
|
|