Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/64656
Authors: 
Robinson, P. M.
Year of Publication: 
2008
Series/Report no.: 
cemmap working paper CWP29/08
Abstract: 
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.
Subjects: 
Spatial dependence
Parameter estimation
Asymptotic theory
Independence testing
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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