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합성 통제 방법 (SCM)×회귀 불연속 설계(Regression Discontinuity Design, RDD)×
분야인과추론인과추론
계열Regression modelRegression model
기원 연도20102008
창시자Abadie, Diamond & HainmuellerImbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
유형Counterfactual causal-inference modelQuasi-experimental causal design
원전Abadie, 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 ↗Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗
별칭synthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM)RDD, regression discontinuity design, sharp RDD, fuzzy RDD
관련55
요약The 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.Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold.
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ScholarGate방법 비교: Synthetic Control · Regression Discontinuity. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare