Targeted policies and household consumption dynamics: Evidence from high-frequency transaction data
利用超过10亿笔家庭支付交易数据，分析了2020年秋季意大利针对性限制政策对消费和疫情传播的影响，发现宽松政策减少消费下降且有效控制感染，为危机中数据驱动决策提供证据。
The COVID-19 pandemic shock heavily affected households and prompted governments to design policies supporting household consumption. Differentiated strategies were among the most commonly adopted policies, targeting territories and economic activities with a stringency consistent with the severity of the contagion. Leveraging a unique dataset of over 1 billion household payment transactions, which captures digital and physical consumption, we provide a retrospective analysis of targeted restrictions in Italy during the fall of 2020. We show that territories implementing less stringent policies exhibit a smaller reduction in consumption and that differentiated restrictions are effective in limiting the spread of infections. Furthermore, in our analyses we account for common factors limiting household consumption choices such as disposable income, liquidity constraints and fear of contagion. Our results demonstrate the effectiveness of targeted restrictions in balancing between economic and public health objectives and call for data-driven and evidence-based policymaking during crises.