Módszerek összehasonlítása
Tekintse át a kiválasztott módszereket egymás mellett; az eltérő sorok kiemelve jelennek meg.
| A gépi tanulással kiegészített szintetikus kontroll módszer× | A különbség-különbségek (Diff-in-Diff) módszer× | |
|---|---|---|
| Tudományterület≠ | Oksági következtetés | Ökonometria |
| Módszercsalád | Regression model | Regression model |
| Keletkezés éve≠ | 2021 | 1994 |
| Megalkotó≠ | Ben-Michael, Feller & Rothstein | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Típus≠ | Causal inference / quasi-experimental | Causal inference / panel regression |
| Alapmű≠ | Ben-Michael, E., Feller, A., & Rothstein, J. (2021). The augmented synthetic control method. Journal of the American Statistical Association, 116(536), 1789-1803. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Alternatív nevek≠ | ML-augmented SCM, augmented synthetic control, ASC, penalized synthetic control | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Kapcsolódó | 5 | 5 |
| Összefoglaló≠ | The machine learning-augmented synthetic control method extends the classical synthetic control estimator by using penalized regression or other ML algorithms — such as lasso, ridge, or random forests — to construct the donor weights and to model pre-treatment outcome trajectories. The augmentation corrects for residual imbalance left by the standard weighting step, yielding lower bias when no perfect synthetic control exists. | 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. |
| ScholarGateAdatkészlet ↗ |
|
|