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Corona, crisis and conditional heteroscedasticity

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  • Tamás Kiss
  • Pär Österholm

Abstract

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.

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  • Tamás Kiss & Pär Österholm, 2021. "Corona, crisis and conditional heteroscedasticity," Applied Economics Letters, Taylor & Francis Journals, vol. 28(9), pages 755-759, May.
    • Handle: RePEc:taf:apeclt:v:28:y:2021:i:9:p:755-759
    DOI: 10.1080/13504851.2020.1776829
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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