Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Metoda syntetické kontroly pro hodnocení politik× | Model panelových dat s fixními efekty× | |
|---|---|---|
| Obor≠ | Kauzální inference | Ekonometrie |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 2003-2010 | 2014 |
| Tvůrce≠ | Alberto Abadie & Javier Gardeazabal; extended by Abadie, Diamond & Hainmueller | Hsiao (textbook treatment); within transformation of panel data |
| Typ≠ | Causal inference / comparative case study | Panel data regression |
| Původní zdroj≠ | 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 ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Další názvy | Synthetic Control Method, SCM, Synthetic Control, Abadie-Diamond-Hainmueller method | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | The Synthetic Control Method (SCM) is a causal inference technique for evaluating the effect of a policy or intervention on a single treated unit — such as a region, country, or firm — by constructing a weighted combination of untreated comparison units that closely mirrors the treated unit before the intervention. Introduced by Abadie and Gardeazabal (2003) and formalized by Abadie, Diamond, and Hainmueller (2010), it provides a data-driven, transparent counterfactual for comparative case studies. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
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