Novel Method for Estimating Time-Varying COVID-19 Transmission Rate

Hongfei Xiao, Deqin Lin () and Shiyu Li
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Hongfei Xiao: Faculty of Finance, City University of Macau, Macau 999078, China
Deqin Lin: Faculty of Finance, City University of Macau, Macau 999078, China
Shiyu Li: Faculty of Finance, City University of Macau, Macau 999078, China

Mathematics, 2023, vol. 11, issue 10, 1-18

Abstract: The transmission rate is an important indicator for characterizing a virus and estimating the risk of its outbreak in a certain area, but it is hard to measure. COVID-19, for instance, has greatly affected the world for more than 3 years since early 2020, but scholars have not yet found an effective method to obtain its timely transmission rate due to the fact that the value of COVID-19 transmission rate is not constant but dynamic, always changing over time and places. Therefore, in order to estimate the timely dynamic transmission rate of COVID-19, we performed the following: first, we utilized a rolling time series to construct a time-varying transmission rate model and, based on the model, managed to obtain the dynamic value of COVID-19 transmission rate in mainland China; second, to verify the result, we used the obtained COVID-19 transmission rate as the explanatory variable to conduct empirical research on the impact of the COVID-19 pandemic on China’s stock markets. Eventually, the result revealed that the COVID-19 transmission rate had a significant negative impact on China’s stock markets, which, to some extent, confirms the validity of the used measurement method in this paper. Notably, the model constructed in this paper, combined with local conditions, can not only be used to estimate the COVID-19 transmission rate in mainland China but also in other affected countries or regions and would be applicable to calculate the transmission rate of other pathogens, not limited to COVID-19, which coincidently fills the gaps in the research. Furthermore, the research based on this model might play a part in regulating anti-pandemic governmental policies and could also help investors and stakeholders to make decisions in a pandemic setting.

Keywords: COVID-19 transmission rate; rolling time series; dynamic time series; stock market (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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