Causal estimation of COVID-19 and SARS on China's stock market: evidence from a time series counterfactual prediction

Yun Feng and Xin Li

Economic Research-Ekonomska Istraživanja, 2022, vol. 35, issue 1, 1734-1751

Abstract: This investigation infers the time evolution causal effect of COVID-19 and SARS on China's stock market based on predicting the counterfactual market response using a diffusion-regression state-space model. The results show that SARS caused an average negative impact of 5.4% on stock prices. In comparison, COVID-19 had a negative impact of 5.3%. Furthermore, considering China's growing worldwide influence, this study carefully reselects the covariates and finds that the negative impact of COVID-19 on stock prices has conservatively increased to 10%, far stronger than the impact of SARS. The results show that the quantitative estimation of the causal effect of emergencies such as COVID-19 must be based on reliable counterfactual inference; only relying on statistical correlation measures may lead to biased estimation. The analysis of the time evolution characteristics of the causal effect shows that the negative impact caused by COVID-19 began to weaken within three days, while the impact of SARS lasted longer. The results show that the Chinese government's strict lockdown achieved the effect of stopping losses in time, and this finding helps to provide a positive demonstration for worldwide epidemic response strategies.

Date: 2022
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DOI: 10.1080/1331677X.2021.1910533

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