In the current context of the COVID-19 pandemic, working from home (WFH) became of great importance for a large share of employees since it represents the only option to both continue working and minimise the risk of virus exposure. Uncertainty about the duration of the pandemic and future contagion waves even led companies to view WFH as a 'new normal' way of working. Based on influence function regression methods, this paper explores the potential consequences in the labour income distribution related to a long-lasting increase in WFH feasibility among Italian employees. Results show that a positive shift in WFH feasibility would be associated with an increase in average labour income, but this potential benefit would not be equally distributed among employees. Specifically, an increase in the opportunity to WFH would favour male, older, high-educated, and high-paid employees. However, this 'forced innovation' would benefit more employees living in provinces have been more affected by the novel coronavirus. WFH thus risks exacerbating pre-existing inequalities in the labour market, especially if it will not be adequately regulated. As a consequence, this study suggests that policies aimed at alleviating inequality, like income support measures (in the short run) and human capital interventions (in the long run), should play a more important compensating role in the future.

We analyse the content of Italian occupations operating in about 600 sectors with a focus on the dimensions that expose workers to risks during the COVID-19 epidemics. We leverage detailed information from ICP, the Italian equivalent of O*Net and find that several sectors need physical proximity to operate: the workers employed in sectors whose physical proximity index is above the national average are more than 6.5 million (mostly in retail trade). Groups at risk of complications from COVID-19 (mainly male above the age of 50) work in sectors that are little exposed to physical proximity, currently under lockdown or can work remotely. The sectoral lockdowns put in place by the Italian Government in March 2020 targeted sectors that operate in physical proximity, but not those directly exposed to infections (the health industry is not subject to lockdown). Most of the workforce who can operate from home have not been put under lockdown.

We analyze the task-content of occupations operating in about 600 sectors of the economy with a focus on the dimensions that expose workers to contagion risks during the COVID-19 epidemic. We do so in the Italian context, leveraging extremely detailed and granular information from ICP, the Italian equivalent of O*Net (the survey that describes the task content of US occupations). We find that several sectors need physical proximity to operate, mainly in services and retail trade. Workers at risk of complications from COVID-19 (mainly males above the age of 50) are concentrated in sectors characterized by little physical proximity or where working from home is feasible. We then study the sectoral lockdowns put in place by the Italian Government in March 2020. We find that governmental restrictions hit the sectors where the risk of contagion in the workplace was more widespread: the effect is stronger for proximity to the public than that with co-workers. The share of workers who have the possibility to work from home is higher in sectors that were not forced to close. The evidence we provide is useful to identify which activities pose larger risks for contagion among workers in the workplace and where to reinforce safety measures.

Italy was among the first countries to introduce drastic measures to reduce mobility in order to prevent the diffusion of Covid-19. On March 9, 26 out of 111 provinces were subject to severe limitations on individual mobility and social interactions. One day later, new restrictive measures were introduced in the whole country with no regional distinctions: this continued until June 3 when the limits on movements across regions were eventually lifted. By looking at these watershed moments, this paper explores, for the first time, the impact of the adoption and the removal of restrictive measures on changes in individual mobility in Italy. By using a spatial discontinuity approach, we show that these measures were effective in that they lowered individual mobility by about 7 percentage points relative to what is accounted for by the characteristics of the local population and the disease. The analysis shows, however, that local features played an important role after the travel bans were lifted: the catching up with pre-Covid-19 patterns has been stronger in those areas where the labour force is relatively less exposed to the risk of contagion and less likely to work from home.