手法を比較

	政策評価のための介入時系列分析	合成コントロール法（SCM）
分野	因果推論	因果推論
系統	Regression model	Regression model
提唱年	1975 (intervention analysis); 2000s–2010s (policy evaluation framing)	2003–2010
提唱者	Box & Tiao (1975); popularised for policy by Shadish, Cook & Campbell (2002) and Bernal et al. (2017)	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
種類	Quasi-experimental causal design	Quasi-experimental causal inference
原典	Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355.	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.
別名	ITS for policy evaluation, policy ITS, segmented regression for policy, policy impact ITS	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
関連	4	4
概要	Interrupted Time Series (ITS) for policy evaluation uses routinely collected aggregate time-series data to estimate the causal impact of a policy change. A segmented regression model splits the series at a known intervention date, estimating both an immediate level shift and a change in trend attributable to the policy — without requiring a randomised control group.	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.