Сравнение методов

	Пространственный метод синтетического контроля	Разность разностей (Difference-in-Differences, DiD)
Область	Причинно-следственный вывод	Эконометрика
Семейство	Regression model	Regression model
Год появления	2003–2010s	1994
Автор метода	Abadie & Gardeazabal (2003); extended to spatial settings by subsequent applied econometric work	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Тип	Quasi-experimental causal inference	Causal inference / panel regression
Основополагающий источник	Abadie, A., & Gardeazabal, J. (2003). The Economic Costs of Conflict: A Case Study of the Basque Country. American Economic Review, 93(1), 113-132.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Другие названия	spatial SCM, geographic synthetic control, spatial SC, spatial counterfactual control	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Связанные	6	5
Сводка	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.	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.