Study on Impacts of COVID-19 Pandemic Recession Based on Monte Carlo Simulation

Di Shang, Chang Yu and Gang Diao

Prague Economic Papers, 2021, vol. 2021, issue 6, 724-747

Abstract: We analyse the economic impact of the economic recession caused by the unprecedented COVID-19 pandemic by estimating the amplitude, duration and scope of influence of the recession. We employ the turning point method to extract the characteristics of the historical recessions since 1980 in 153 countries and use the information to obtain the distribution characteristics of the GDP growth rate in these countries during the current pandemic-induced recession with Monte Carlo simulation. We then make judgment on the scope of influence of this pandemic-induced recession by investigating the co-movement relationship between the historical recessions in the 153 countries. The results show that this pandemic-induced recession is likely to be a severe global recession. The mean of the average simulated ΔGDP of the 153 countries will plunge into a trough at -1.16% in 2020 with a recession amplitude of approximately 4.50% and recover to the pre-crisis level of 3.29% in 2023.

Keywords: COVID-19 pandemic; economic recession; GDP growth rate forecasting; turning points; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: E30 F60 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.18267/j.pep.786

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