Corona, Crisis and Conditional Heteroscedasticity - Tamás Kiss; Pär Österholm (Örebro University School of Business, 2020)
In this paper, we illustrate the macroeconomic risk associated with the early stage of the corona-virus outbreak. Using monthly data ranging from July 1991 to March 2020 on a recently developed coincidence indicator of global output growth, we estimate an autoregressive model with GARCH effects and non-Gaussian disturbances. Our results indicate that i) accounting for conditional heteroscedasticity is important and ii) risk, measured as the volatility of the shocks to the process, is at a very high level – largely on par with that experienced around the financial crisis of 2008-2009.
Keywords: C22; E32; E37; 330; GARCH; Non-Gaussianity