Large-Sample Inference on Spatial Dependence

19 Pages Posted: 13 May 2009

See all articles by Peter M. Robinson

Peter M. Robinson

London School of Economics & Political Science (LSE) - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: January 2009

Abstract

We consider cross-sectional data that exhibit no spatial correla- tion, 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.

JEL Classification: D74;H77;F13;019

Suggested Citation

Robinson, Peter M., Large-Sample Inference on Spatial Dependence (January 2009). LSE STICERD Research Paper No. EM533, Available at SSRN: https://ssrn.com/abstract=1401782

Peter M. Robinson (Contact Author)

London School of Economics & Political Science (LSE) - Department of Economics ( email )

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