The Influence of Spatially Correlated Heteroskedasticity on Tests for Spatial Correlation

In cross sectional regression models the possibility of spill-overs between neighboring units is increasingly being recognized in both the theoretical and applied literature.1 Within a regression framework, typically recognized forms of such spill-overs relate to the model’s dependent and independent variables, as well as to the error terms. General issues relating to spill-overs suggest that the model's error terms may be spatially correlated. Because the statistical properties of the regression parameter estimators depend upon whether or not the error terms are indeed spatially correlated, tests for such correlation are frequently considered.2