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Método do Controle Sintético (MCS)×Diferenças em Diferenças (DiD)×
ÁreaInferência causalEconometria
FamíliaRegression modelRegression model
Ano de origem2003–20101994
Autor originalAlberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipoQuasi-experimental causal inferenceCausal inference / panel regression
Fonte seminalAbadie, 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 ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Outros nomesSCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller methoddiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Relacionados45
ResumoThe 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.Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.
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ScholarGateComparar métodos: Synthetic Control Method · Difference-in-Differences. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare