Does women´s political empowerment matter for income inequality?

This paper analyzes the endogenous relationship between women's political empowerment and income inequality in a sample of 142 countries between 1990 and 2019. To identify causal effects, we rely on the use of Random Forests techniques and a set of exogenous variables on ancestral and traditional cultural norms of gender roles. These tree-based machine learning statistical techniques help us to predict current women's political empowerment with high accuracy solely using ancestral societal traits. This predicted variable is then used in the second stage of the IV estimation of a panel data specification of income inequality. Our panel-IV regressions show that women's political empowerment reduces income inequality, measured as the Gini index of disposable income. This finding is robust to the presence of spatial interdependence and time persistence in inequality outcomes, as well as to the potential bias due to the omission of unobservable variables, the presence of outliers and inuential observations, and an alternative de_nition of income inequality.