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Large-sample inference on spatial dependence

P. M. Robinson

Econometrics Journal, 2009, vol. 12, issue s1, S68-S82

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. Copyright (C) The Author(s). Journal compilation (C) Royal Economic Society 2009

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:12:y:2009:i:s1:p:s68-s82

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Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms

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