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A Design-Based Approach to Spatial Correlation

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arxiv 2211.14354 v1 pith:MQ37QWHM submitted 2022-11-25 econ.EM

classification econ.EM
keywords spatialstandardcorrelationerrorchannelserrorssamplingshould
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Design-Based Approach to Testing and Inference in (Quasi-)Experiments with Spillovers

    econ.EM 2026-07 conditional novelty 7.0 of 10

    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.

  2. Design-Based and Network Sampling-Based Uncertainties in Network Experiments

    econ.EM 2025-06 conditional novelty 6.0 of 10

    Correlations among exposure-mapping regressors make OLS spillover coefficients weighted sums of heterogeneous effects plus contamination terms, and sampled networks can create such correlations even when the populatio...

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