Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/1708
Title: Modeling Covid-19 Contagion Dynamics: Time-Series Analysis Across Different Countries and Subperiods.
Authors: Mladenović, Zorica
Glavaš, Lenka 
Mladenović, Pavle 
Affiliations: Probability and Mathematical Statistics 
Probability and Mathematical Statistics 
Issue Date: 2023
Rank: M33
Publisher: Springer
Related Publication(s): Theory and Applications of Time Series Analysis and Forecasting : Selected contributions from ITISE 2021
Abstract: 
This study offers two sets of empirical results to model the daily COVID-19 contagion time series. The Markov-switching models with ARMA structure are implemented assuming that time-series dependence is nonlinear, whereas regimes are data-driven. The first set of results consists of models estimated for the following European countries: Italy, Germany, the United Kingdom, and Russia during the first epidemic wave. The second set of results deals with modeling time series for Italy over the second and the third epidemic waves. Given the empirical findings reached, we have distinguished among several regimes during the epidemic wave. The persistence of time series over each regime is also discussed.
URI: https://research.matf.bg.ac.rs/handle/123456789/1708
DOI: 10.1007/978-3-031-14197-3_18
Appears in Collections:Research outputs

Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.