Vertaile menetelmiä
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| Alueellinen synteettinen kontrollimenetelmä× | Synteettisen kontrollin menetelmä (SCM)× | |
|---|---|---|
| Tieteenala | Kausaalipäättely | Kausaalipäättely |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 2003–2010s | 2003–2010 |
| Kehittäjä≠ | Abadie & Gardeazabal (2003); extended to spatial settings by subsequent applied econometric work | Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010) |
| Tyyppi | Quasi-experimental causal inference | Quasi-experimental causal inference |
| Alkuperäislähde≠ | Abadie, A., & Gardeazabal, J. (2003). The Economic Costs of Conflict: A Case Study of the Basque Country. American Economic Review, 93(1), 113-132. 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 ↗ |
| Rinnakkaisnimet | spatial SCM, geographic synthetic control, spatial SC, spatial counterfactual control | SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method |
| Liittyvät≠ | 6 | 4 |
| Tiivistelmä≠ | The Spatial Synthetic Control Method adapts the classic synthetic control framework to settings where treated and donor units are defined by geographic location. By constructing a weighted combination of spatially proximate or comparable control regions, the method estimates what would have happened to a treated area absent the intervention, while explicitly accounting for geographic spillovers, spatial autocorrelation, and contiguity among units. | The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect. |
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