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Mr. Christian Gonzales, Ms. Sonali Jain-Chandra, Ms. Kalpana Kochhar, Ms. Monique Newiak, and Mr. Tlek Zeinullayev

This study shows empirically that gender inequality and income inequality are strongly interlinked, even after controlling for standard drivers of income inequality. The study analyzes gender inequality by using and extending the United Nation’s Gender Inequality Index (GII) to cover two decades for almost 140 countries,. The main finding is that an increase in the GII from perfect gender equality to perfect inequality is associated with an almost 10 points higher net Gini coefficient. For advanced countries, with higher gender equity in opportunities, income inequality arises mainly through gender gaps in economic participation. For emerging market and developing countries, inequality of opportunity, in particular in education and health, appear to pose larger obstacles to income equality.

Mr. Christian Gonzales, Ms. Sonali Jain-Chandra, Ms. Kalpana Kochhar, Ms. Monique Newiak, and Mr. Tlek Zeinullayev
This study shows empirically that gender inequality and income inequality are strongly interlinked, even after controlling for standard drivers of income inequality. The study analyzes gender inequality by using and extending the United Nation’s Gender Inequality Index (GII) to cover two decades for almost 140 countries,. The main finding is that an increase in the GII from perfect gender equality to perfect inequality is associated with an almost 10 points higher net Gini coefficient. For advanced countries, with higher gender equity in opportunities, income inequality arises mainly through gender gaps in economic participation. For emerging market and developing countries, inequality of opportunity, in particular in education and health, appear to pose larger obstacles to income equality.
Mr. Serhan Cevik and João Tovar Jalles

.023) 0.025 (0.021) Ln(pop) (t-1) -0.529*** (0.131) -0.703*** (0.156) -0.001 (0.094) -0.210* (0.127) Ln(pop_den) (t-1) 0.488*** (0.135) 0.689*** (0.161) -0.008 (0.096) 0.203 (0.128) Fixed effects Yes Yes Yes Yes Observations 1,241 1,241 874 874 R-squared 0.975 0.987 0.986 0.989 Note: The dependent variable is income inequality as measured by gross and net Gini coefficient and identified in the second row. *, **, *** denote statistical significance at the 10, 5 and 1 percent levels

Davide Furceri, Mr. Prakash Loungani, Mr. Jonathan David Ostry, and Pietro Pizzuto

, Loungani, Ostry and Pizzuto (2020) follow the method proposed by Jordà (2005) and estimate impulse response functions directly from local projections: y i , t + k = α i k + γ t k + β k D i , t + θ k X i , t + ϵ i , t + k ( 1 ) where y i,t is the market or net Gini coefficient, or redistribution, for country i in year t ; α i are country fixed effects, included to take account of differences in countries’ average income distribution; γ t are time fixed effects, included to take account of global shocks such as shifts in oil prices or the global

Andras Komaromi

to decrease by about 5 percent relative to the income of the bottom decile of the income distribution. This estimated effect appears statistically significant for the earlier vintages, but for the latest available cross-section of data it becomes insignificant. Panels 3c and 3d show the estimated effect of trade openness on the market and net Gini coefficients, respectively. Again, almost all of the point estimates suggest an inequality reducing effect of trade. For example, a one percentage point higher openness is associated with a 0.2-0.6 points lower net Gini