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	Difference-in-Differences nella Ricerca sull'Istruzione	Metodo del Controllo Sintetico (SCM)
Campo	Inferenza causale	Inferenza causale
Famiglia	Regression model	Regression model
Anno di origine	1990s–2000s	2003–2010
Ideatore	Dynarski, Card, Angrist, and colleagues — applied in education economics from the 1990s onward	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Tipo	Quasi-experimental causal inference	Quasi-experimental causal inference
Fonte seminale	Dynarski, S. M. (2003). Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion. American Economic Review, 93(1), 279-288.	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.
Alias	DiD in education, education DiD, quasi-experimental education design, education policy DiD	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Correlati	5	4
Sintesi	Difference-in-Differences (DiD) in education research applies the classic quasi-experimental DiD estimator to evaluate education policies, programs, and reforms. Researchers compare changes in student, school, or district outcomes between a group exposed to an intervention and a comparable unexposed group across pre- and post-intervention periods, isolating policy effects from background trends.	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.