在新冠肺炎中生存:中国商城流量恢复曲线

Cheng He, Tong Wang, Xiaopeng Luo, Zhenzhi Luo, J. Guan, Haojun Gao, Keyan Zhu, lu feng, Yuehao Xu, Yuan Cheng, Y. Hu
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引用次数: 0

摘要

新冠肺炎疫情给世界经济带来巨大冲击。随着一些国家在控制疫情方面取得进展,其中一些国家已开始重新开放经济。我们使用来自中国88个城市的463家商场的每日客流量的独特实时数据集,研究了经济重新开放后的复苏曲线。我们的研究结果表明,在重新开放经济9周后,商场客流量已恢复到疫情前的64.0%。此外,遏制疫情的进展,如报告零新发本地病例和清除所有现有病例,可大大促进商场交通的恢复。此外,我们发现不同城市的复苏遵循不同的曲线,这种异质性可以用疫情、城市等级和城市特征(如人口、GDP、产业结构等)来解释。具体而言,在疫情较好、城市层级较低、流动人口较少、第三产业比重较低、第二产业比重较高、人均国内生产总值较高的城市,恢复速度较快。
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Surviving COVID-19: Recovery Curves of Mall Traffic in China
The outbreak of COVID-19 has caused huge disruptions to the world economy. As a number of countries make progress in containing this outbreak, some of them have started to reopen their economy. We study the curves of recovery after reopening the economy, using a unique real-time dataset of daily customer traffic of 463 malls from 88 cities in China. Our results demonstrate that 9 weeks after reopening the economy, mall traffic has recovered to 64.0% of its level before this outbreak. In addition, the progress of containing this outbreak, such as reporting zero new local cases and clearing all existing cases, could significantly boost the recovery of mall traffic. Furthermore, We find that the recovery follows different curves across different cities, and this heterogeneity can be explained by pandemic situations, city tiers and city characteristics such as population, GDP, industrial structure, etc. More specifically, faster recovery speeds are observed in cities with better pandemic situations, lower city tiers, smaller migrant population, lower proportion of tertiary industry, higher proportion of secondary industry and higher GDP per capita.
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