方法对比

	教育研究中的反事实影响评估	合成控制法 (SCM)
领域	因果推断	因果推断
方法族	Regression model	Regression model
起源年份	2000s–2010s	2003–2010
提出者	Blundell & Costa Dias; formalized for EU education policy by the European Commission Joint Research Centre	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
类型	Quasi-experimental causal inference framework	Quasi-experimental causal inference
开创性文献	Blundell, R., & Costa Dias, M. (2002). Alternative approaches to evaluation in empirical microeconomics. Portuguese Economic Journal, 1(2), 91-115.	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.
别名	CIE in education, counterfactual program evaluation, causal impact evaluation, education policy impact evaluation	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
相关	5	4
摘要	Counterfactual impact evaluation (CIE) is the systematic application of causal inference designs — such as difference-in-differences, regression discontinuity, matching, and instrumental variables — to measure the genuine effect of education programs, policies, or interventions by constructing a credible counterfactual: what would have happened to participants had they not been treated.	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.