A correctly specified exposure map implies design-side orthogonality conditions, so the exposure radius can be estimated by GMM and tested by overidentification — rejecting the 2 km radius in the GiveDirectly experiment.
A Design-Based Approach to Spatial Correlation
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
When observing spatial data, what standard errors should we report? With the finite population framework, we identify three channels of spatial correlation: sampling scheme, assignment design, and model specification. The Eicker-Huber-White standard error, the cluster-robust standard error, and the spatial heteroskedasticity and autocorrelation consistent standard error are compared under different combinations of the three channels. Then, we provide guidelines for whether standard errors should be adjusted for spatial correlation for both linear and nonlinear estimators. As it turns out, the answer to this question also depends on the magnitude of the sampling probability.
fields
econ.EM 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
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A Design-Based Approach to Testing and Inference in (Quasi-)Experiments with Spillovers
A correctly specified exposure map implies design-side orthogonality conditions, so the exposure radius can be estimated by GMM and tested by overidentification — rejecting the 2 km radius in the GiveDirectly experiment.