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Händelsestudiedesign inom utbildningsforskning×Syntetisk kontrollmetod (SCM)×
ÄmnesområdeKausal inferensKausal inferens
FamiljRegression modelRegression model
Ursprungsår1993 (general); 2000s–2010s (education applications)2010
UpphovspersonJacobson, LaLonde & Sullivan (1993); popularized in education by Lafortune, Rothstein & Schanzenbach (2018) and subsequent education-policy literatureAbadie, Diamond & Hainmueller
TypQuasi-experimental / causal inferenceCounterfactual causal-inference model
UrsprungskällaJacobson, L. S., LaLonde, R. J., & Sullivan, D. G. (1993). Earnings Losses of Displaced Workers. American Economic Review, 83(4), 685-709. link ↗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 ↗
Aliasevent study, education event study, policy event study, dynamic difference-in-differencessynthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM)
Närliggande55
SammanfattningAn event study design tracks how educational outcomes evolve before and after a clearly defined event — such as a school finance reform, accountability policy, or curriculum change — for affected and unaffected units. By estimating period-by-period treatment effects relative to a baseline period, it delivers both a causal estimate of the policy's impact and a transparent test of the parallel-trends assumption underpinning difference-in-differences.The 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.
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ScholarGateJämför metoder: Event Study Design in Education Research · Synthetic Control. Hämtad 2026-06-19 från https://scholargate.app/sv/compare