Documents Brussevich, Mariya 2 results

"Using individual level data on task composition at work for 30 advanced and emerging economies, we find that women, on average, perform more routine tasks than men?tasks that are more prone to automation. To quantify the impact on jobs, we relate data on task composition at work to occupation level estimates of probability of automation, controlling for a rich set of individual characteristics (e.g., education, age, literacy and numeracy skills). Our results indicate that female workers are at a significantly higher risk for displacement by automation than male workers, with 11 percent of the female workforce at high risk of being automated given the current state of technology, albeit with significant cross-country heterogeneity. The probability of automation is lower for younger cohorts of women, and for those in managerial positions."

"Unpaid work, such as caring for children, the elderly, and household chores represents a significant share of economic activity but is not counted as part of GDP. Women disproportionately shoulder the burden of unpaid work: on average, women do two more hours of unpaid work per day than men, with large differences across countries. While much unpaid care work is done entirely by choice, constraints imposed by cultural norms, labor market features or lack of public services, infrastructure, and family-friendly policies matter. This undermines female labor force participation and lowers economy-wide productivity. In this paper, we examine recent trends in unpaid work around the world using aggregate and individual-level data, explore potential drivers, and identify policies that can help reduce and redistribute unpaid work across genders. Conservative model-based estimates suggest that the gains from these policies could amount to up to 4 percent of GDP."