Regression modelSpatial causal inference

Spatial Difference-in-Differences

Spatial Difference-in-Differences (Spatial DiD) extends the classical DiD estimator to settings where observations are geo-referenced and outcomes may be spatially autocorrelated or subject to spillover effects. Introduced by Delgado and Florax (2015), the method augments the standard two-way fixed-effects DiD regression with a spatial lag or spatial error term, yielding unbiased treatment-effect estimates even when policy shocks propagate across geographic units. It is used by economists, regional scientists, and urban planners evaluating place-based interventions such as infrastructure investment, environmental regulations, or zoning reforms.

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Sources

  1. Delgado, M. S., & Florax, R. J. G. M. (2015). Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction. Economics Letters, 126, 35–40. DOI: 10.1016/j.econlet.2014.10.035

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Referenced by

ScholarGateSpatial Difference-in-Differences (Spatial Difference-in-Differences). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/spatial-difference-in-differences