The COVID-19 pandemic and lockdowns have led to a rise in gender-based violence. In this paper, we explore the economic consequences of violence against women in sub-Saharan Africa using large demographic and health survey data collected pre-pandemic. Relying on a two-stage least square method to address endogeneity, we find that an increase in the share of women subject to violence by 1 percentage point can reduce economic activities (as proxied by nightlights) by up to 8 percent. This economic cost results from a significant drop in female employment. Our results also show that violence against women is more detrimental to economic development in countries without protective laws against domestic violence, in natural resource rich countries, in countries where women are deprived of decision-making power and during economic downturns. Beyond the moral imperative, the findings highlight the importance of combating violence against women from an economic standpoint, particularly by reinforcing laws against domestic violence and strengthening women’s decision-making power.
This paper presents a novel technique to measure and compare the redistributive capacity of observed tax (or transfer) policies. The technique is based on income distribution simulations and controls for differences in pre-tax income distributions. It assumes that the only information on the pre-tax distribution available in each country-year is the Gini coefficient and the mean (GDP per capita). We illustrate the technique with an application to the personal income tax, using a dataset of 108 countries over the 2007-2018 period.