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Spatial Synthetic Control Method×Spatial Interrupted Time Series×
ÄmnesområdeKausal inferensKausal inferens
FamiljRegression modelRegression model
Ursprungsår2003–2010s1990s–2000s
UpphovspersonAbadie & Gardeazabal (2003); extended to spatial settings by subsequent applied econometric workExtension of McDowall et al. (1980) ITS framework; spatial adaptations developed in epidemiology and geography through the 1990s–2000s
TypQuasi-experimental causal inferenceQuasi-experimental causal inference with spatial adjustment
UrsprungskällaAbadie, A., & Gardeazabal, J. (2003). The Economic Costs of Conflict: A Case Study of the Basque Country. American Economic Review, 93(1), 113-132. DOI ↗McDowall, D., McCleary, R., Meidinger, E. E., & Hay, R. A. (1980). Interrupted Time Series Analysis. Sage Publications. ISBN: 978-0803913950
Aliasspatial SCM, geographic synthetic control, spatial SC, spatial counterfactual controlSpatial ITS, Geospatial ITS, Spatially-adjusted ITS, SITS
Närliggande66
SammanfattningThe 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.Spatial Interrupted Time Series (Spatial ITS) extends the classic ITS design to settings where units are geo-referenced and outcomes in one location may spill over into or correlate with outcomes in neighbouring locations. It estimates the causal effect of a discrete intervention on an outcome time series while explicitly modelling geographic autocorrelation, preventing biased standard errors and enabling detection of spatial spillovers.
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ScholarGateJämför metoder: Spatial Synthetic Control Method · Spatial Interrupted Time Series. Hämtad 2026-06-18 från https://scholargate.app/sv/compare