| Summary/Abstract |
The spread of the novel coronavirus (COVID-19) has had a major political, economic, social, and cultural impact on various countries worldwide. Based on economic operation, public opinion, public health, government policies and population inflow in the affected areas, this study measures daily economic resilience during the COVID-19 outbreak in 286 prefecture-level cities in China (from 1st January to 8th February, 2020). Specifically, this study further investigates the economic resilience and the number of COVID-19 cases by analysing the evolutionary trend of their spatial distribution pattern using the standard deviation ellipse (SDE). The impact of COVID-19 on economic resilience is examined using a panel vector autoregressive model. The following are the findings. (1) The economic resilience value decreased throughout the study period, but the cities with high economic resilience showed a trend of spatial diffusion in the late study period. Wuhan’s lockdown strategy was benefit to control the spread of COVID-19, and promptly stopped the decline of China's economic resilience. (2) Economic resilience and the number of COVID-19 cases influenced their future trends positively, but this effect gradually decreased over time. During the COVID-19, although the number of confirmed cases significantly influenced China's economic resilience, and the disease's spread was evident, China maintained a high level of economic development resilience. (3) The rise in economic resilience during the pandemic's early stages promoted the number of confirmed cases, but the strength of this relationship gradually declined as the pandemic progressed. Returning to work and other activities may increase the risk of infection. Numerous policies implemented at the outbreak’ inception aided in laying the groundwork for economic resilience. Although the outbreak had a detrimental effect on economic resilience in the later stages of the pandemic, a convergent trend was observed at the end of the research period. (4) Using variance decomposition, we discovered that future economic resilience was significantly influenced by itself and by relatively few changes. However, the impact of confirmed cases on economic resilience becomes apparent after the fourth period. This indicates that the number of confirmed cases must be limited during the initial stages. The early support of various sectors in China facilitated the spatial expansion of economically resilient cities. The pandemic has a non-negligible negative impact on economic resilience, but this has been mitigated by Wuhan's timely closure.
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