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패널 데이터 합성 통제법×합성 통제 방법 (SCM)×
분야인과추론인과추론
계열Regression modelRegression model
기원 연도20102003–2010
창시자Alberto Abadie, Alexis Diamond & Jens HainmuellerAlberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
유형Causal inference / panel dataQuasi-experimental causal inference
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 ↗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 ↗
별칭SCM panel, panel synthetic control, synthetic control estimator, comparative case studySCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
관련54
요약The panel data synthetic control method estimates the causal effect of an intervention on a single treated unit by constructing a data-driven weighted combination of untreated units — a synthetic control — that best reproduces the treated unit's pre-treatment outcome trajectory. The post-treatment gap between the treated unit and its synthetic counterpart is the estimated treatment effect.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.
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