Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Метод на синтетичен контрол (SCM)× | Инструментални променливи чрез двуетапни най-малки квадрати (IV/2SLS)× | |
|---|---|---|
| Област | Причинно-следствено заключение | Причинно-следствено заключение |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2010 | 2009 |
| Създател≠ | Abadie, Diamond & Hainmueller | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| Тип≠ | Counterfactual causal-inference model | Instrumental-variables regression |
| Основополагащ източник≠ | 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 ↗ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Други названия≠ | synthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM) | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| Свързани | 5 | 5 |
| Резюме≠ | The Synthetic Control Method, introduced by Abadie, Diamond and Hainmueller in 2010, builds a weighted counterfactual for a single treated unit from a pool of untreated donor units. It is widely regarded as the gold standard for evaluating large policy interventions, natural experiments, and N=1 case studies where no obvious comparison unit exists. | IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009). |
| ScholarGateНабор от данни ↗ |
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