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Metóda syntetickej kontroly panelových dát×Odhadovač založený na párovaní×
OdborKauzálna inferenciaKauzálna inferencia
RodinaRegression modelRegression model
Rok vzniku20101973
TvorcaAlberto Abadie, Alexis Diamond & Jens HainmuellerRubin (1973); large-sample theory by Abadie & Imbens (2006)
TypCausal inference / panel dataNonparametric matching / causal inference
Pôvodný zdrojAbadie, 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., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267. DOI ↗
Ďalšie názvySCM panel, panel synthetic control, synthetic control estimator, comparative case studynearest-neighbor matching, NNM, matching on covariates, covariate matching
Príbuzné56
ZhrnutieThe 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 matching estimator identifies the causal effect of a treatment by pairing each treated unit with one or more untreated units that have similar observed characteristics. Formalised by Rubin (1973) and given rigorous large-sample theory by Abadie and Imbens (2006), it constructs a credible control group from observational data without requiring a parametric model for the outcome.
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ScholarGatePorovnať metódy: Panel Data Synthetic Control Method · Matching Estimator. Získané 2026-06-18 z https://scholargate.app/sk/compare