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| Metodo del Controllo Sintetico nella Ricerca sull'Educazione× | Modello a Effetti Fissi per Dati Panel× | |
|---|---|---|
| Campo≠ | Inferenza causale | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2003-2010 | 2014 |
| Ideatore≠ | Alberto Abadie, Alexis Diamond, and Jens Hainmueller | Hsiao (textbook treatment); within transformation of panel data |
| Tipo≠ | Quasi-experimental causal inference | Panel data regression |
| Fonte seminale≠ | 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 ↗ |
| Alias | SCM in education, synthetic control, synthetic comparator, SCM | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Correlati | 5 | 5 |
| Sintesi≠ | The Synthetic Control Method (SCM) estimates the causal effect of an education policy or intervention by constructing a weighted combination of untreated comparison units — the synthetic control — that closely mimics the treated unit's pre-intervention trajectory. Developed by Abadie, Diamond, and Hainmueller, it is especially valuable when only one or a small number of schools, districts, or countries receive a policy change and no natural comparison exists. | 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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