In response to the coronavirus disease 2019 (COVID-19) pandemic, several national governments have applied lockdown restrictions to reduce the infection rate. Here we perform a massive analysis on near–real-time Italian mobility data provided by Facebook to investigate how lockdown strategies affect economic conditions of individuals and local governments. We model the change in mobility as an exogenous shock similar to a natural disaster. We identify two ways through which mobility restrictions affect Italian citizens. First, we find that the impact of lockdown is stronger in municipalities with higher fiscal capacity. Second, we find evidence of a segregation effect, since mobility contraction is stronger in municipalities in which inequality is higher and for those where individuals have lower income per capita. Our results highlight both the social costs of lockdown and a challenge of unprecedented intensity: On the one hand, the crisis is inducing a sharp reduction of fiscal revenues for both national and local governments; on the other hand, a significant fiscal effort is needed to sustain the most fragile individuals and to mitigate the increase in poverty and inequality induced by the lockdown.

为了应对2019年冠状病毒疾病（COVID-19）大流行，一些国家政府已实施封锁限制以降低感染率。在这里，我们对Facebook提供的近实时意大利流动性数据进行了大规模分析，以研究锁定策略如何影响个人和地方政府的经济状况。我们将流动性变化建模为类似于自然灾害的外来冲击。我们确定了流动限制对意大利公民的两种影响方式。首先，我们发现，在财政能力较高的城市，封锁的影响更大。其次，我们发现了隔离效应的证据，因为在不平等程度较高的城市以及人均收入较低的城市，流动性收缩更为强烈。我们的结果凸显了封锁的社会成本和前所未有的严峻挑战：一方面，这场危机导致国家和地方政府的财政收入急剧减少；另一方面，需要大量的财政努力来维持最脆弱的个人，并减轻因封锁而造成的贫困和不平等现象的增加。