Modeling Covid-19 Contagion Dynamics: Time-Series Analysis Across Different Countries and Subperiods.

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.