Dash Devi Prasad, Sethi Narayan
School of Management and Entrepreneurship, Indian Institute of Technology, Jodhpur, Rajasthan, India.
Department of Humanities and Social Sciences, National Institute of Technology, Rourkela, Odisha, India.
MethodsX. 2023 Aug 25;11:102347. doi: 10.1016/j.mex.2023.102347. eCollection 2023 Dec.
Utilizing a daily data of 29 Asian Economies from June 2021 to June 2022, this study investigates the impacts of economic growth, health infrastructures and Government measures on COVID-19 cases. Our results demonstrate that GDP, Government intervention, testing and vaccination exert positive impacts on COVID-19 cases. We incorporate factors like weather to know how temperature impacts COVID-19 Cases. Our results demonstrate that magnitude of COVID-19 cases goes on upward fashion in winter days more. With reference to co-morbid conditions like diabetes, we notice that people with diabetes are more vulnerable to the infections, however due to the greater behavioral response, we obtain a negative association between co-morbid conditions and new COVID-19 cases. However, the intensity of COVID-19 cases is decimated with the improvement in health facilities and behavioral changes. Besides basic regression estimates, our instrumental variable estimates hold true in the line of regression results while underlying the relation with the COVID-19 cases. Interestingly, our results from alternate specification ensures that high human development with greater openness has resulted in more COVID-19 cases. Overall, our study belies the fact that vaccination and higher govt intervention can prevent COVID-19. Rather, a comprehensive policy is recommended on cross-country basis to overcome such challenge.•The Study analyzes the relation among COVID-19, economic growth and health infrastructure on a daily basis from June 2021 to June 2022 for 29 Asian Economies•Our empirical strategy involves regression followed by robustness tests of instrumental variable regression model.•Results show that higher growth, human development, lesser vaccination and trivial govt intervention post 2020 have resulted in more COVID-19 cases.
本研究利用2021年6月至2022年6月期间29个亚洲经济体的每日数据，调查经济增长、卫生基础设施和政府措施对新冠疫情病例的影响。我们的结果表明，国内生产总值、政府干预、检测和疫苗接种对新冠疫情病例产生积极影响。我们纳入了天气等因素，以了解温度如何影响新冠疫情病例。我们的结果表明，冬季新冠疫情病例的数量增长更为明显。关于糖尿病等合并症，我们注意到糖尿病患者更容易感染，但由于行为反应更强，我们发现合并症与新增新冠疫情病例之间存在负相关。然而，随着卫生设施的改善和行为变化，新冠疫情病例的强度有所下降。除了基本回归估计外，我们的工具变量估计在回归结果中也成立，同时揭示了与新冠疫情病例的关系。有趣的是，我们从替代规格得出的结果确保了更高的人类发展水平和更大的开放度导致了更多的新冠疫情病例。总体而言，我们的研究表明，疫苗接种和更高的政府干预并不能预防新冠疫情。相反，建议在跨国基础上制定全面政策来应对这一挑战。
•该研究分析了2021年6月至2022年6月期间29个亚洲经济体每日新冠疫情、经济增长和卫生基础设施之间的关系
•我们的实证策略包括回归，然后对工具变量回归模型进行稳健性检验。
•结果表明，2020年后更高的经济增长、人类发展水平、较低的疫苗接种率和微不足道的政府干预导致了更多的新冠疫情病例。
