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

Abstract

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.

Keywords: Contagion; Covid-19; Health; Information; Internal migration networks; Mobility; Virus.

Fig. 1

Exposure to outbreak, local mobility and pop. Inflows by province-week. Notes: the figure is based on a regression of log trips within a province per 1000 inhabitants (Panel A) and IHS trips from outbreak areas per 1000 inhabitants (Panel B) on log exposure to outbreak interacted with week dummies, date FEs, region-week FEs, province controls interacted with week dummies, and province FEs. Geographic controls include: log distance to outbreak provinces, number of square kilometers, altitude, share of seaside cities. Socio-demographic controls include: population density, share of males, number of intensive care hospital beds per 100,000 inhabitants, whether there is an airport, share of urban areas, population share above 70 years, population share with high school education or higher, population share with university education. Economic controls include: number of firms per capita, value added per capita, median financial wealth, median income. Total migration is the log of the number of people who moved from the province to any other area in the country between 2015 and 2018 (per 1000 inhabitants). Dashed lines represent 95 percent confidence intervals. Standard errors are adjusted for spatial correlation (a‘ la Conley, with 100 km threshold) and serial correlation. Dates on the $x$-axis indicate the beginning of the week. The estimates correspond to Table A.2, Column 4, and Table A.3, Column 4.

Fig. 2

Exposure to outbreak, local mobility and population inflows across Northern and Southern regions. Notes: the figure is based on a regression of log trips within a province per 1000 inhabitants (Panel A) and IHS trips from outbreak areas per 1000 inhabitants (Panel B) on log exposure to outbreak interacted with South/North and week dummies, date FEs, region-week FEs, and province controls interacted with week dummies. Province controls as in Fig. 1. Dashed lines represent 95 percent confidence intervals. Standard errors adjusted for spatial correlation (a‘ la Conley, with 100 km threshold) and serial correlation. Dates on the $x$-axis indicate the beginning of the week.