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Raumzeitliche synthetische Kontrollmethode×Differenz-in-Differenzen (DiD)×
FachgebietKausale InferenzÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr2003–2010s1994
UrheberAbadie & Gardeazabal (2003); extended to spatial settings by subsequent applied econometric workCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypQuasi-experimental causal inferenceCausal inference / panel regression
Wegweisende QuelleAbadie, A., & Gardeazabal, J. (2003). The Economic Costs of Conflict: A Case Study of the Basque Country. American Economic Review, 93(1), 113-132. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Aliasnamenspatial SCM, geographic synthetic control, spatial SC, spatial counterfactual controldiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Verwandt65
ZusammenfassungThe Spatial Synthetic Control Method adapts the classic synthetic control framework to settings where treated and donor units are defined by geographic location. By constructing a weighted combination of spatially proximate or comparable control regions, the method estimates what would have happened to a treated area absent the intervention, while explicitly accounting for geographic spillovers, spatial autocorrelation, and contiguity among units.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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ScholarGateMethoden vergleichen: Spatial Synthetic Control Method · Difference-in-Differences. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare