School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China.
School of Economics, Huazhong University of Science and Technology, Wuhan, China; Research Associate, MUSLIM Institute, Islamabad, Pakistan.
J Infect Public Health. 2021 Oct;14(10):1411-1426. doi: 10.1016/j.jiph.2021.08.008. Epub 2021 Aug 13.
Restrictive measures enacted in response to the COVID-19 pandemic have resulted in dramatic and substantial variations in people's travel habits and behaviors worldwide. This paper empirically examines the asymmetric inter-linkages between transportation mobility and COVID-19.
Using daily data from 1st March 2020 to 15th July 2020, this study draws the dynamic and causal relationships between transportation mobility and COVID-19 in ten selected countries (i.e., USA, Brazil, Mexico, UK, Spain, Italy, France, Germany, Canada, and Belgium). To systematically analyze how the quantiles of COVID-19 (transportation mobility) affect the quantiles of transportation mobility (COVID-19), a complete set of non-linear modeling including the quantile-on-quantile (QQ) regression and quantile Granger causality in mean is applied.
Our preliminary findings strictly reject the preposition of data normality and highlight that the observed relationship is highly correlated and quantile-dependent. The empirical results demonstrate the heterogeneous dependence between COVID-19 and transportation mobility across quantiles. The findings acclaim the presence of a significant positive association between COVID-19 and transportation mobility in the USA, UK, Spain, Italy, Canada, France, Germany and Belgium, predominantly at upper quantiles, but results are contrasting in the case of Brazil and Mexico. In addition, either lower or upper quantiles of both variables indicate a declining negative effect of transportation mobility on COVID-19. Furthermore, the outcomes of quantile Granger causality in mean conclude a bidirectional causal link between COVID-19 and transportation mobility for almost all sample countries. Unlike them, France has found unidirectional causality that extends from COVID-19 to transportation mobility.
We may conclude that COVID-19 leads to a reduction in transportation mobility. On the other hand, the empirical results quantify that excessive transportation mobility levels stimulate pandemic cases, and social distancing is one of the primary measures to encounter infection transmission. Imperative country-specific policy implications pertaining to public health, potential virus spread, transportation, and the environment may be drawn from these findings.
为应对 COVID-19 大流行而采取的限制措施导致全球范围内人们的旅行习惯和行为发生了巨大而显著的变化。本文实证检验了交通流动性与 COVID-19 之间的非对称相互联系。
本研究使用 2020 年 3 月 1 日至 2020 年 7 月 15 日的每日数据，分析了十个选定国家（美国、巴西、墨西哥、英国、西班牙、意大利、法国、德国、加拿大和比利时）的交通流动性与 COVID-19 之间的动态和因果关系。为了系统地分析 COVID-19（交通流动性）的分位数如何影响交通流动性（COVID-19）的分位数，应用了一套完整的非线性模型，包括分位数-分位数（QQ）回归和分位数均值格兰杰因果关系。
我们的初步研究结果严格否定了数据正态性的假设，并强调观察到的关系高度相关且与分位数相关。实证结果表明，COVID-19 和交通流动性在分位数之间存在异质依赖性。研究结果表明，在美国、英国、西班牙、意大利、加拿大、法国、德国和比利时，COVID-19 与交通流动性之间存在显著的正相关关系，主要出现在较高的分位数上，但在巴西和墨西哥的情况则相反。此外，两个变量的较低或较高分位数都表明交通流动性对 COVID-19 的负效应呈下降趋势。此外，均值分位数格兰杰因果关系的结果得出，几乎所有样本国家的 COVID-19 和交通流动性之间存在双向因果关系。与它们不同的是，法国发现了从 COVID-19 到交通流动性的单向因果关系。
我们可以得出结论，COVID-19 导致交通流动性下降。另一方面，实证结果量化了过度的交通流动性水平会刺激疫情病例，而保持社交距离是应对感染传播的主要措施之一。可以根据这些发现制定有关公共卫生、潜在病毒传播、交通和环境的具体国家政策。
