The Economic Cost of Locking down like China: Evidence from City-to-City Truck Flows

Replication package for "The Economic Cost of Locking down like China: Evidence from City-to-City Truck Flows".<br>Abstract: Containing the COVID-19 pandemic by non-pharmacological interventions is costly. Using high-frequency, city-to-city truck flow data, this paper estimates the economic cost of lockdown in China, a stringent yet effective policy prior to the Omicron surge. By comparing the truck flow change in the cities with and without lockdown, we find that a one-month full-scale lockdown causally reduces the truck flows connected to the locked down city in the month by 54%, implying a decline of the city’s real income with the same proportion in a gravity model of city-to-city trade. We also structurally estimate the cost of lockdown in the gravity model, where the effects of lockdown can spill over to other cities through trade linkages. Imposing full-scale lockdown on the four largest cities in China (Beijing, Shanghai, Guangzhou, and Shenzhen) for one month would reduce the real national GDP by 8.7%, of which 8.5% is contributed by the spillover effects.

《效仿中国封控的经济成本：基于城市间货车流量的实证证据》一文的复现数据集包<br>摘要：通过非药物干预（non-pharmacological interventions）遏制新冠疫情需付出高昂代价。本文采用高频城市间货车流量数据，估算了中国在奥密克戎疫情暴发前实施的严苛且有效的封控政策的经济成本。通过对比封控与未封控城市的货车流量变化，研究发现：为期1个月的全面封控将使封控城市当月的连通货车流量因果性减少54%；在城市间贸易引力模型（gravity model）中，这意味着该城市实际收入将出现同等幅度的下滑。本文还在引力模型框架下对封控的经济成本进行了结构性估算，其中封控的影响可通过贸易联动渠道溢出至其他城市。若对中国四大城市（Beijing, Shanghai, Guangzhou, and Shenzhen）实施为期1个月的全面封控，将使全国实际GDP减少8.7%，其中8.5%的损失由溢出效应贡献。