Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Перервний часовий ряд для панельних даних× | Різниця різниць (Diff-in-Diff)× | |
|---|---|---|
| Галузь≠ | Причинно-наслідковий висновок | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2000s–2010s | 1994 |
| Автор методу≠ | Shadish, Cook & Campbell (design framework); Bernal, Cummins & Gasparrini (epidemiological tutorial) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Тип≠ | Quasi-experimental causal inference | Causal inference / panel regression |
| Основоположне джерело≠ | Lopez Bernal, J., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Інші назви≠ | panel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Пов'язані | 5 | 5 |
| Підсумок≠ | Panel Data Interrupted Time Series (panel ITS) is a quasi-experimental method that estimates the causal effect of an intervention using repeated observations from multiple units over time. By exploiting variation across both units and time periods, it provides stronger causal identification than single-unit ITS, detecting changes in the level and slope of the outcome trajectory immediately following a clearly dated intervention. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
| ScholarGateНабір даних ↗ |
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