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This paper decomposes the gender gap in pay in the Russian Federation along the earnings distribution for the period 1996-2011. The analysis uses a reweighted, recentered influence function decomposition that allows estimating the contribution of each covariate on the wage structure and composition effects along the earnings distribution. The paper finds that women are in flat career paths compared with men; the importance of observable characteristics that proxy human capital in the gender pay gap decrease along the earnings distribution; and if women's pay took into account their educational degrees as much as men's, the gender pay gap would disappear or even reverse at the top of the earnings distribution. The results suggest that women at the bottom of the earnings distribution should be helped to increase their labor market skills, and women at the top of the distribution should be helped to break the glass ceiling and be remunerated for their skills to the same extent as men.

Gender --- Gender & development --- Gender pay gap --- Health, nutrition and population --- Labor markets --- Labor policies --- Population policies --- Recentered influence function --- Rif decomposition --- Rif regression --- RLMS --- Rural development --- Rural development knowledge and information systems --- Russian federation --- Social protections and labor

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In Armenia, the proportion of women among employed workers increased from 45 to 48 percent between 2008 and 2015. This evolution was accompanied by a fall in the gender earnings gap; however, the difference in average wages of men and women is still among the largest in comparison with countries in the Europe and Central Asia region. This study documents the gender wage gap in Armenia through stylized facts and further investigates its sources. The paper finds that the gender wage gap in hourly pay is 20 percent on average. Looking at the different percentiles, the disparity in wages in Armenia in 2015 shows an inverted U-shaped form with a larger differential in wages between men and women in the middle of the distribution. Using a reweighted, re-centered influence function decomposition, the analysis estimates the contribution of each covariate on the wage structure and composition effects along the wage distribution. The decomposition shows that the wage gap in Armenia is mostly driven by the wage structure effect (unexplained component), which accounts for almost all the wage gap in the middle part of the distribution (30th to 55th percentiles) and is even greater at the top, but better endowments of women offset it to some extent. In the bottom part of the distribution however, the composition effect is larger, consistent with lower endowments among women, for example, of skills and human capital.

Education --- Educational Sciences --- Gender --- Gender & Development --- Inequality --- Labor Markets --- Poverty Reduction --- Social Protections and Labor --- Wage --- Wage Gap --- Wage Inequality --- Wages Compensation & Benefits