Regression modelQuasi-experimental / causal inference

Spatial Causal Impact Analysis

Spatial causal impact analysis estimates the causal effect of a spatially-targeted intervention — a policy, shock, or treatment applied to particular locations — while explicitly accounting for geographic spillovers between treated and untreated units. By combining quasi-experimental designs such as difference-in-differences or regression discontinuity with spatial econometric models, it separates the direct local effect of a treatment from indirect effects that diffuse to neighbouring areas.

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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, 137, 123-126. DOI: 10.1016/j.econlet.2015.10.035
  2. Halleck Vega, S., & Elhorst, J. P. (2015). The SLX Model. Journal of Regional Science, 55(3), 339-363. DOI: 10.1111/jors.12188

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Referenced by

ScholarGateSpatial Causal Impact Analysis (Spatial Causal Impact Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/spatial-causal-impact-analysis