论文标题
使用人类流动数据量化Covid-19在中国大陆的经济影响
Quantifying the Economic Impact of COVID-19 in Mainland China Using Human Mobility Data
论文作者
论文摘要
为了遏制中国大陆冠状病毒（Covid-19）的大流行，当局已经采取了一系列措施，包括隔离，社会疏远和旅行限制。 While these strategies have effectively dealt with the critical situations of outbreaks, the combination of the pandemic and mobility controls has slowed China's economic growth, resulting in the first quarterly decline of Gross Domestic Product (GDP) since GDP began to be calculated, in 1992. To characterize the potential shrinkage of the domestic economy, from the perspective of mobility, we propose two new economic indicators: the New Venues Created (NVC) and the使用百度地图的数据，作为国内投资和消费活动的互补措施，对场地的访问（v^3）量（v^3）。这两个指标的历史记录表明与中国GDP的过去数字有很强的相关性，而由于大流行，今年的现状发生了巨大变化。我们在此提出了一种定量分析，以使用NVC和V^3的最新趋势来投射大流行对经济体的影响。我们发现，受影响最大的部门将是旅行依赖的企业，例如酒店，教育机构和公共交通工具，而人类生活必须强制的行业，例如工作场所，住宅区，餐馆，餐馆和购物地点，一直在迅速康复。省级的分析表明，具有内部供应，生产和消费的自给自足和自我维持的经济区域比依靠全球供应链的那些地区更快地恢复了。
To contain the pandemic of coronavirus (COVID-19) in Mainland China, the authorities have put in place a series of measures, including quarantines, social distancing, and travel restrictions. While these strategies have effectively dealt with the critical situations of outbreaks, the combination of the pandemic and mobility controls has slowed China's economic growth, resulting in the first quarterly decline of Gross Domestic Product (GDP) since GDP began to be calculated, in 1992. To characterize the potential shrinkage of the domestic economy, from the perspective of mobility, we propose two new economic indicators: the New Venues Created (NVC) and the Volumes of Visits to Venue (V^3), as the complementary measures to domestic investments and consumption activities, using the data of Baidu Maps. The historical records of these two indicators demonstrated strong correlations with the past figures of Chinese GDP, while the status quo has dramatically changed this year, due to the pandemic. We hereby presented a quantitative analysis to project the impact of the pandemic on economies, using the recent trends of NVC and V^3. We found that the most affected sectors would be travel-dependent businesses, such as hotels, educational institutes, and public transportation, while the sectors that are mandatory to human life, such as workplaces, residential areas, restaurants, and shopping sites, have been recovering rapidly. Analysis at the provincial level showed that the self-sufficient and self-sustainable economic regions, with internal supplies, production, and consumption, have recovered faster than those regions relying on global supply chains.
