Social capital and the spread of coronavirus in Europe

Like many researchers, I've been closely following the emerging research on the coronavirus pandemic, and looking to contribute to it. With some colleagues, I've been looking at how social capital might be related to the success (or otherwise) of lockdown policies, and the effect on coronavirus infections and deaths. The idea was intuitive - reducing infection rates essentially requires that people act in the best interests of society, so (holding other relevant factors constant) countries or regions with higher social capital should be suffering less, with fewer infections and coronavirus-related deaths.

Unfortunately, our data analysis to date hasn't been showing anything of interest, which we have put down to measurement error in the data. However, this new working paper by Alina Kristin Bartscher (University of Bonn) and co-authors offers a sensible explanation for our null results:

From a theoretical perspective, social capital, the spread of Covid-19 and containment policies interact in various ways. First, high-social-capital areas are known to be more vibrant and better connected, economically and socially... Hence, we expect the virus to spread more quickly in those areas in the beginning of the pandemic, when information about the virus and its severity were incomplete. Second, as soon as the importance of behavioral containment norms becomes more salient, we expect the relationship to change... we expect that informal rules of containment are more likely to be (voluntarily) adopted in areas with high social capital, leading to a relative decrease in infections.

In our analysis, we had adopted a cross-sectional approach to try to overcome some of the measurement issues with the high-frequency data. However, in adopting that approach we were conflating the early period, when the relationship between social capital and infections is expected to be positive, with the later period, when the relationship is expect to be negative. It should be no surprise then, that we were finding null results!

Anyway, the Bartscher et al. paper uses data for seven European countries (Austria, Germany, Italy, the Netherlands, Sweden, Switzerland and the UK), and uses electoral turnout in the European elections (or local elections for Switzerland) as a measure of social capital. They also use a number of different measures (both social capital, and outcome measures) for Italy. They found that:

First, the number of Covid-19 cases is initially higher in high-social-capital areas. Second, as information on the virus spreads, high-social- capital areas start to show a slower increase in Covid-19 cases in all seven countries. Third, high-social-capital areas also exhibit a slower growth in excess deaths in Italy. Fourth, individual mobility is reduced more strongly before the lockdown in Italian high-social-capital areas. Fifth, we provide suggestive evidence that the role of social capital is reduced when national lockdowns are enforced, as the differences in mobility between high- and low-social-capital areas vanish after the national lockdown is enacted.

More specifically, the found that high-social capital regions have between 12 percent and 32 percent fewer cumulative coronavirus cases. When they look at Italy in more detail, they found that one standard deviation higher social capital (electoral turnout) is associated with 7 percent lower excess mortality, and a 15 percent reduction is mobility. The latter result demonstrates the likely mechanism through which social capital leads to fewer deaths - people in areas with more social capital adhere more closely to the lockdown rules that people in areas with less social capital.

Overall, Bartscher et al. conclude that:

...the consistent pattern obtained from independent analyses of seven countries as strong evidence in favor of the hypothesis that social capital plays an important role in slowing down the spread of the virus.

This is probably not the last word on this line or research. Bartscher et al.'s approach of simply comparing regions above and below the median level of social capital within the country is rather crude, even though the results are as expected. It would be interesting to see whether the results hold when social capital is treated as a continuous measure rather than simply categorising high/low social capital areas. It would also be interesting to see if similar results are obtained for counties in the U.S. No doubt we will see analysis of U.S. counties sometime in the future.