This research will address whether and how the coronavirus pandemic exacerbates barriers to gender parity in developing countries by asymmetrically affecting time use for men and women. The effects of COVID-19 are likely to differ by gender (Alon et al., 2020), but the nature and extent of those differences are uncertain. The study, therefore, proposes the collection and creation of a novel dataset, based on a short survey combined with 90-day web browsing histories of individuals from Nigeria and Ghana, to empirically assess the differential effects of COVID-19 on time use by gender.
Women traditionally bear a greater responsibility for childcare and home production, for both cultural and economic reasons. The study, therefore, hypothesizes that the outbreak, and associated closures to schools and businesses, will present a larger shock to the time budgets of women and tend to disproportionately increase their unpaid work and dampen their work productivity. At the same time, the pandemic can cause demand shocks that differ by gender because of occupational sex segregation. Women tend to be highly represented in essential service sector jobs that need to be performed onsite (Gupta 2020, Robertson and Gebellof 2020), which would imply a smaller change in time use during work hours, but possibly larger shifts in time outside of paid work. The study, therefore, expects the gendered effects to differ based on the work status and occupation of the adults in the household, which they will examine with data from our survey. They will also assess whether investments-to-self–such as job search and skills development –are differentially affected by the pandemic for men and women. Our results can help assess the impact of the pandemic on gender parity and point to areas for potential policy intervention.
The researchers aim to enroll 1000 participants from Nigeria and Ghana. They have selected those countries because of the availability of online marketing panels in those countries and relatively higher rates of internet penetration compared to other African countries. Our decision to include two countries rather than one is based on the importance of timely data collection for our identification strategy that relies on collecting pre-Covid-19 data. They aim to recruit about500 participants from each country, but the shares will depend on how quickly they can collect data from each country.
Our design is compatible with social distancing, using internet technology for data collection. They have obtained IRB clearance for this research project and have signed a contract with this data provider to obtain similar data in India, using other funding obtained this week. Our technology tracks the last 90days of websites visited from a user account, combining data from multiple device logins, such as mobile phone, and personal and office computers. This feature allows us to observe changes over time for the same individual, before and after the pandemic becomes salient. Crucially, the web traffic data have time stamps and can be assigned to categories: this allows us to identify timing and duration of work-related activities (e.g., visiting a company website), leisure activities (e.g., Facebook) and time spent offline.