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合成対照法(SCM)×マッチング手法(CEM / 最適 / ジェネティック)×
分野因果推論因果推論
系統Regression modelRegression model
提唱年20102012
提唱者Abadie, Diamond & HainmuellerIacus, King & Porro (CEM); Hansen (optimal/full matching)
種類Counterfactual causal-inference modelMatching for causal inference
原典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. DOI ↗Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗
別名synthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM)coarsened exact matching, optimal matching, genetic matching, CEM
関連55
概要The Synthetic Control Method, introduced by Abadie, Diamond and Hainmueller in 2010, builds a weighted counterfactual for a single treated unit from a pool of untreated donor units. It is widely regarded as the gold standard for evaluating large policy interventions, natural experiments, and N=1 case studies where no obvious comparison unit exists.Matching Methods are a family of causal-inference techniques beyond propensity-score matching that pair treated and control units with similar covariates so that a treatment effect can be read off the balanced sample. The family includes Coarsened Exact Matching (Iacus, King & Porro, 2012), optimal matching, and genetic matching.
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ScholarGate手法を比較: Synthetic Control · Matching Methods. 2026-06-17に以下より取得 https://scholargate.app/ja/compare