Internal migration networks and mortality in home communities: Evidence from Italy during the Covid-19 pandemic.

Do internal migration networks benefit or harm their home communities in case of a communicable disease? Looking at the spread of Covid in Italy and using pre-determined province-to-province migration, excess mortality and mobile phone tracking data, we document that provinces with a greater share of migrants in outbreak areas show greater compliance with self-isolation measures (information mechanism), but also a greater population inflow from outbreak areas (carrier mechanism). For a subset of localities, the net effect on mortality is negative. However, for the average locality, the effect is positive and large, suggesting that the role of migrants as information providers is trumped by their role as virus carriers. The effect is quantitatively important and could be incorporated in epidemiological models forecasting the spread of communicable diseases.

Tracking the impact of COVID-19 on economic inequality at high frequency.

Pandemics have historically had a significant impact on economic inequality. However, official inequality statistics are only available at low frequency and with considerable delay, which challenges policymakers in their objective to mitigate inequality and fine-tune public policies. We show that using data from bank records it is possible to measure economic inequality at high frequency. The approach proposed in this paper allows measuring, timely and accurately, the impact on inequality of fast-unfolding crises, like the COVID-19 pandemic. Applying this approach to data from a representative sample of over three million residents of Spain we find that, absent government intervention, inequality would have increased by almost 30% in just one month. The granularity of the data allows analyzing with great detail the sources of the increases in inequality. In the Spanish case we find that it is primarily driven by job losses and wage cuts experienced by low-wage earners. Government support, in particular extended unemployment insurance and benefits for furloughed workers, were generally effective at mitigating the increase in inequality, though less so among young people and foreign-born workers. Therefore, our approach provides knowledge on the evolution of inequality at high frequency, the effectiveness of public policies in mitigating the increase of inequality and the subgroups of the population most affected by the changes in inequality. This information is fundamental to fine-tune public policies on the wake of a fast-moving pandemic like the COVID-19.

Asocial capital: Civic culture and social distancing during COVID-19.

Social distancing can slow the spread of COVID-19 if citizens comply with it and internalize the cost of their mobility on others. We study how civic values mediate this process using data on mobility across Italian provinces between January and May 2020. We find that after the virus outbreak mobility declined, but significantly more in areas with higher civic capital, both before and after a mandatory national lockdown. The effect is not driven by differences in the risk of contagion, health-care capacity, geographic socioeconomic and demographic factors, or by a general North-South divide. Simulating a SIR model calibrated on Italy, we estimate that if all provinces had the same civic capital as those in top-quartile, COVID-related deaths would have been about 60% lower. We find consistent results for Germany where the incidence of the pandemic and restrictions to mobility were milder.