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	Metodo del Controllo Sintetico nella Ricerca sull'Educazione	Difference-in-Differences (Diff-in-Diff)
Campo	Inferenza causale	Econometria
Famiglia	Regression model	Regression model
Anno di origine	2003-2010	1994
Ideatore	Alberto Abadie, Alexis Diamond, and Jens Hainmueller	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Tipo	Quasi-experimental causal inference	Causal inference / panel 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.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Alias	SCM in education, synthetic control, synthetic comparator, SCM	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
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.	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.