Otto, P. , Doğan, O. and Taşpınar, S. (2023) Dynamic spatiotemporal ARCH models. Spatial Economic Analysis, (doi: 10.1080/17421772.2023.2254817) (Early Online Publication)
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Abstract
Geo-referenced data are characterised by an inherent spatial dependence due to geographical proximity. In this paper, we introduce a dynamic spatiotemporal autoregressive conditional heteroscedasticity (ARCH) process to describe the effects of (i) the log-squared time-lagged outcome variable, the temporal effect, (ii) the spatial lag of the log-squared outcome variable, the spatial effect, and (iii) the spatiotemporal effect on the volatility of an outcome variable. We derive a generalised method of moments (GMM) estimator based on the linear and quadratic moment conditions. We show the consistency and asymptotic normality of the GMM estimator. After studying the finite-sample performance in simulations, the model is demonstrated by analysing monthly log-returns of condominium prices in Berlin from 1995 to 2015, for which we found significant volatility spillovers.
| Item Type: | Articles |
|---|---|
| Status: | Early Online Publication |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Otto, Dr Philipp |
| Authors: | Otto, P., Doğan, O., and Taşpınar, S. |
| College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | Spatial Economic Analysis |
| Publisher: | Taylor & Francis |
| ISSN: | 1742-1772 |
| ISSN (Online): | 1742-1780 |
| Published Online: | 20 October 2023 |
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