This study examines gender-based differences in the effects of the COVID-19 pandemic lockdowns on digital time use and activity in Kenya. The authors collected novel data online during the lockdown, combining survey responses from 316 Kenyans with their individual internet browser histories spanning the prior 90 days. This data set includes over 3.9 million unique website visits, providing an objective record of time use that is free from intentional misreporting or recall bias, and which was easier to collect than subjective time use data, which was greatly hindered by the lockdown. By combining browser and survey data, the authors are able to measure gender differences in the impact of the lockdown for different sub-groups. By identifying the key variables – gender and local broadband speed – that they used for their sub-population analyses and their estimates of differential impacts, the researchers were able to characterize the sample population along a wide range of attributes, which could be compared with those of the overall Kenyan population.
An analysis of the lockdown period revealed a significant increase in browser time for the overall sample, with an average of 41 minutes per person-day in levels and 0.15 points on a logarithmic scale. Further examination of the effects of the lockdown on women and those with high-speed broadband, relative to men and those with low-speed broadband, revealed no significant differences in total browser time between the two subgroups. However, there were significant changes in the content consumed. Women experienced a substantial increase in time spent on Netflix, with an average of over 35 minutes per day per person more than men. Additionally, people with faster broadband speed spent more time on LinkedIn, which could suggest future divergent labor market outcomes.
Throughout the March – June 2020 sample period, women and people in areas with high-speed internet spent substantially more time online than men and those in areas with low-speed internet, respectively. This finding is in contrast to the results of Miller et al. (2021), which were derived from a similarly gathered sample of PC users in India, where men spent significantly more time online. Although the women in both of these samples were slightly less likely to be employed, the Kenyan sample revealed that women were twice as likely to be single, which may partially explain the higher time online. They observed a significant increase in overall browser usage after the first Covid-19 lockdown. The detailed data revealed distinct disparities when examining specific domains, despite no discernible difference in overall usage by gender.
Kenya is a nation with high gender disparities, and women around the world have been disproportionately affected by the Covid-19 pandemic. This paper revealed that women engaged more in self-investment activities than men, post-lockdown. This is particularly true for the relatively younger, unmarried women in the sample, which is a positive sign for the advancement of women in Kenya in the future. Read the detailed working paper here.