A dynamic spatiotemporal stochastic volatility model with an application to environmental risks

Otto, P. , Doğan, O. and Taşpınar, S. (2023) A dynamic spatiotemporal stochastic volatility model with an application to environmental risks. Econometrics and Statistics, (doi: 10.1016/j.ecosta.2023.11.002) (In Press)

[img] Text
309142.pdf - Published Version
Available under License Creative Commons Attribution.

6MB

Abstract

A dynamic spatiotemporal stochastic volatility (SV) model is introduced, incorporating explicit terms accounting for spatial, temporal, and spatiotemporal spillover effects. Alongside these features, the model encompasses time-invariant site-specific factors, allowing for differentiation in volatility levels across locations. The statistical properties of an outcome variable within this model framework are examined, revealing the induction of spatial dependence in the outcome variable. Additionally, a Bayesian estimation procedure employing the Markov Chain Monte Carlo (MCMC) approach, complemented by a suitable data transformation, is presented. Simulation experiments are conducted to assess the performance of the proposed Bayesian estimator. Subsequently, the model is applied in the domain of environmental risk modeling, addressing the scarcity of empirical studies in this field. The significance of climate variation studies is emphasized, illustrated by an analysis of local air quality in Northern Italy during 2021, which underscores pronounced spatial and temporal clusters and increased uncertainties/risks during the winter season compared to the summer season.

Item Type:Articles
Status:In Press
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:Econometrics and Statistics
Publisher:Elsevier
ISSN:2452-3062
ISSN (Online):2452-3062
Published Online:08 November 2023
Copyright Holders:Copyright © 2023 The Author(s)
First Published:First published in Econometrics and Statistics 2023
Publisher Policy:Reproduced under a Creative Commons license

University Staff: Request a correction | Enlighten Editors: Update this record