विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहु-अवधि कृत्रिम नियंत्रण विधि× | डायनामिक सिंथेटिक कंट्रोल मेथड (Dynamic Synthetic Control Method)× | |
|---|---|---|
| क्षेत्र | कारणात्मक अनुमान | कारणात्मक अनुमान |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2010-2021 | 2010 |
| प्रवर्तक≠ | Abadie, Diamond & Hainmueller (2010); extended to multi-period settings by Abadie (2021) and Ben-Michael et al. (2021) | Abadie, Diamond & Hainmueller (2010); dynamic extensions by Abadie (2021) and others |
| प्रकार≠ | Quasi-experimental causal inference | Comparative case study / counterfactual estimation |
| मौलिक स्रोत≠ | Abadie, A. (2021). Using synthetic controls: Feasibility, data requirements, and methodological aspects. Journal of Economic Literature, 59(2), 391-425. DOI ↗ | 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 ↗ |
| उपनाम | multi-period SCM, extended synthetic control, synthetic control with multiple treatment periods, staggered synthetic control | Dynamic SCM, Time-varying synthetic control, Multi-period synthetic control, DSC |
| संबंधित | 5 | 5 |
| सारांश≠ | The multi-period synthetic control method extends the classic synthetic control framework to settings where treatment occurs across several distinct periods or where the researcher needs to track causal effects over a prolonged post-treatment window. It constructs a weighted combination of untreated units that reproduces the treated unit's pre-treatment trajectory, then uses that synthetic counterfactual across all post-treatment periods to estimate time-varying treatment effects. | The Dynamic Synthetic Control Method extends the classic synthetic control framework to evaluate treatments that unfold over multiple periods or change in intensity over time. It constructs a weighted combination of untreated units that matches the treated unit in pre-treatment outcomes, then traces the full time path of treatment effects period by period after the intervention — capturing not just an average effect but how the effect evolves dynamically. |
| ScholarGateडेटासेट ↗ |
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