Krisztin Tamás, Piribauer Philipp, Wögerer Michael
International Institute for Applied Systems Analysis (IIASA), Schloßplatz 1, 2361 Laxenburg, Austria.
Austrian Institute of Economic Research (WIFO), Vienna, Austria.
Lett Spat Resour Sci. 2020;13(3):209-218. doi: 10.1007/s12076-020-00254-1. Epub 2020 Aug 1.
In this paper we use spatial econometric specifications to model daily infection rates of COVID-19 across countries. Using recent advances in Bayesian spatial econometric techniques, we particularly focus on the time-dependent importance of alternative spatial linkage structures such as the number of flight connections, relationships in international trade, and common borders. The flexible model setup allows to study the intensity and type of spatial spillover structures over time. Our results show notable spatial spillover mechanisms in the early stages of the virus with international flight linkages as the main transmission channel. In later stages, our model shows a sharp drop in the intensity spatial spillovers due to national travel bans, indicating that travel restrictions led to a reduction of cross-country spillovers.
在本文中,我们使用空间计量经济学方法对各国新冠疫情的每日感染率进行建模。利用贝叶斯空间计量经济学技术的最新进展,我们特别关注诸如航班连接数量、国际贸易关系和共同边界等替代空间联系结构随时间变化的重要性。灵活的模型设置使我们能够研究空间溢出结构随时间的强度和类型。我们的结果表明,在病毒传播的早期阶段,存在显著的空间溢出机制,其中国际航班连接是主要传播渠道。在后期阶段,我们的模型显示,由于国家旅行禁令,空间溢出强度急剧下降,这表明旅行限制导致跨国溢出减少。