Exploiting Locally Exogeneous Variation in Spatial Data: Linear Regression with Many Small Units
Christopher W. Engh
Abstract
This article shows how researchers can exploit locally exogeneous variation even in the presence of endogeneity, autocorrelation, or spurious correlation. It describes the infill asymptotic properties of generalized least squares estimation with county-level data, Census tract-level data, and similar regional averages, including sufficient conditions for consistency, asymptotic normality, and valid inference.
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