Sharma Nonita, Yadav Sourabh, Mangla Monika, Mohanty Anee, Satpathy Suneeta, Mohanty Sachi Nandan, Choudhury Tanupriya
Dr. B.R. Ambedkar National Institute of Technology Jalandhar, Jalandhar, India.
Gautam Buddha University, Greater Noida, India.
GeoJournal. 2021 Oct 23:1-15. doi: 10.1007/s10708-021-10520-4.
This manuscript presents a geospatial and temporal analysis of the COVID'19 along with its mortality rate worldwide and an empirical evaluation of social distance policies on economic activities. Stock Market Indices, Purchasing Manager Index (PMI), and Stringency Index values are evaluated with respect to rising COVID-19 cases based on the collected data from Jan 2020 to June 2021. The findings for the stock market index reveal the highest negative correlation coefficient value, i.e., -0.2, for the Shanghai index, representing a negative relation on stock markets, whereas the value of the correlation coefficient is minimum for Indian markets, i.e., 0.3, indicating the most impact by COVID-19 spread. Further, the results concerning PMI show that the highest value of the correlation coefficient is for the China i.e., -0.52, points to the sharpest pace of contraction. This reflects the lower value of the correlation indicating that the economy is on the way of growth, which can be seen from the PMI value of the various countries. The manuscript presents a novel geospatial model by empirically evaluating the correlation coefficient of COVID-19 with stock market index, PMI, and stringency index to understand the effect of COVID-19 on the global economy.
本手稿对全球范围内的新冠疫情及其死亡率进行了地理空间和时间分析，并对社会距离政策对经济活动的影响进行了实证评估。基于2020年1月至2021年6月收集的数据，针对新冠病例增加情况对股票市场指数、采购经理人指数（PMI）和严格指数值进行了评估。股票市场指数的研究结果显示，上证综指的负相关系数值最高，即-0.2，表明股市存在负相关关系，而印度市场的相关系数值最小，为0.3，表明受新冠疫情传播影响最大。此外，关于PMI的结果表明，中国的相关系数值最高，为-0.52，表明收缩速度最快。这反映出相关系数值较低，表明经济正处于增长阶段，从各国的PMI值中可以看出这一点。本手稿通过实证评估新冠疫情与股票市场指数、PMI和严格指数的相关系数，提出了一种新颖的地理空间模型，以了解新冠疫情对全球经济的影响。
