摘要翻译：
各国政府为遏制新冠肺炎病毒传播而实施的大规模遏制措施在全球经济中造成了巨大的供需冲击。在这里，我们使用经验船只跟踪数据和一种新开发的算法来估计疫情前八个月的全球海上贸易损失。我们的研究结果表明，在港口层面上存在广泛的贸易损失，中国、中东和西欧港口的绝对损失最大，这与特定供应链（如石油、汽车制造）的崩溃有关。总体而言，我们估计2020年前八个月全球海上贸易减少了-7.0%至-9.6%，相当于约2.06亿至2.86亿吨的数量损失和高达2250亿至4120亿美元的价值损失。渔业、矿业和采石业、电气设备和机械制造业、运输设备制造业受到的冲击最大，损失高达11.8%。此外，我们发现损失的地域差异很大，一些小岛屿发展中国家和低收入经济体遭受的相对贸易损失最大。我们发现与新冠肺炎相关的商业和公共交通关闭对全国出口产生了明显的负面影响。总体而言，我们展示了经济活动的实时指标如何支持政府和国际组织的经济复苏努力，并向受影响最严重的经济体和部门分配资金。
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英文标题：
《The implications of large-scale containment policies on global maritime
  trade during the COVID-19 pandemic》
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作者：
Jasper Verschuur, Elco Koks, Jim Hall
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最新提交年份：
2020
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  The implementation of large-scale containment measures by governments to contain the spread of the COVID-19 virus has resulted in a large supply and demand shock throughout the global economy. Here, we use empirical vessel tracking data and a newly developed algorithm to estimate the global maritime trade losses during the first eight months of the pandemic. Our results show widespread trade losses on a port level with the largest absolute losses found for ports in China, the Middle-East and Western Europe, associated with the collapse of specific supply-chains (e.g. oil, vehicle manufacturing). In total, we estimate that global maritime trade reduced by -7.0% to -9.6% during the first eight months of 2020, which is equal to around 206-286 million tonnes in volume losses and up to 225-412 billion USD in value losses. The fishery, mining and quarrying, electrical equipment and machinery manufacturing, and transport equipment manufacturing sectors are hit hardest, with losses up to 11.8%. Moreover, we find a large geographical disparity in losses, with some small islands developing states and low-income economies suffering the largest relative trade losses. We find a clear negative impact of COVID-19 related business and public transport closures on country-wide exports. Overall, we show how real-time indicators of economic activity can support governments and international organisations in economic recovery efforts and allocate funds to the hardest hit economies and sectors.
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