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Robinson, P. M.
Year of Publication: 
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cemmap working paper CWP29/08
We consider cross-sectional data that exhibit no spatial correlation, but are feared to be spatially dependent. We demonstrate that a spatial version of the stochastic volatility model of financial econometrics, entailing a form of spatial autoregression, can explain such behaviour. The parameters are estimated by pseudo Gaussian maximum likelihood based on log-transformed squares, and consistency and asymptotic normality are established. Asymptotically valid tests for spatial independence are developed.
Spatial dependence
Parameter estimation
Asymptotic theory
Independence testing
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Working Paper

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