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Kaedah Kawalan Sintetik (SCM)×Reka Bentuk Pecahan Regresi (RDD)×
BidangInferens KausalInferens Kausal
KeluargaRegression modelRegression model
Tahun asal20102008
PengasasAbadie, Diamond & HainmuellerImbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
JenisCounterfactual causal-inference modelQuasi-experimental causal design
Sumber perintisAbadie, 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 ↗
Aliassynthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM)RDD, regression discontinuity design, sharp RDD, fuzzy RDD
Berkaitan55
RingkasanThe 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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ScholarGateBandingkan kaedah: Synthetic Control · Regression Discontinuity. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare