Stochastic properties of spatial and spatiotemporal ARCH models

Otto, P. , Schmid, W. and Garthoff, R. (2021) Stochastic properties of spatial and spatiotemporal ARCH models. Statistical Papers, 62(2), pp. 623-638. (doi: 10.1007/s00362-019-01106-x)

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Abstract

In this paper, we provide some results on the class of spatial autoregressive conditional heteroscedasticity (ARCH) models, which have been introduced in recent literature to model spatial conditional heteroscedasticity. That means that the variance in some locations depends on the variance in neighboring locations. In contrast to the temporal ARCH model, for which the distribution is known, given the full information set for the prior periods, the distribution is not straightforward in the spatial and spatiotemporal settings. Thus, we focus on the probability structure of these models. In particular, we derive the conditional and unconditional moments of the process as well as the distribution of the process, given a known error distribution. Eventually, it is shown that the process is strictly stationary under certain conditions.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Otto, Dr Philipp
Authors: Otto, P., Schmid, W., and Garthoff, R.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Statistical Papers
Publisher:Springer
ISSN:0932-5026
ISSN (Online):1613-9798
Published Online:06 April 2019

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