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A simple test for spatial heteroscedasticity in spatially varying coefficient models

In spatially varying coefficient models, there has been a common assumption of homoscedasticity. In many practical situations, however, rarely can we know a priori whether this assumption is true or not. In this paper, we propose a simple test for detecting spatial heteroscedasticity in spatially varying coefficient models. Specifically, the testing procedure is constructed based on the square root of the absolute value of the residuals obtained by the local linear geographically weighted estimation. Simulation experiments are conducted to evaluate the performance of the proposed method and the results demonstrate that the method in the paper is quite robust to the types of the error distributions and is more powerful in some cases, especially when the sample size is not very large. A real-world data set is analyzed to demonstrate the application of the proposed test method and the paper is ended with a final remark.