Gender income disparity in the USA: analysis and dynamic modelling

Ivan Kitov and Oleg Kitov

Papers from arXiv.org

Abstract: We analyze and develop a quantitative model describing the evolution of personal income distribution, PID, for males and females in the U.S. between 1930 and 2014. The overall microeconomic model, which we introduced ten years ago, accurately predicts the change in mean income as a function of age as well as the dependence on age of the portion of people distributed according to the Pareto law. As a result, we have precisely described the change in Gini ratio since the start of income measurements in 1947. The overall population consists of two genders, however, which have different income distributions. The difference between incomes earned by male and female population has been experiencing dramatic changes over time. Here, we model the internal dynamics of men and women PIDs separately and then describe their relative contribution to the overall PID. Our original model is refined to match all principal gender-dependent observations. We found that women in the U.S. are deprived of higher job positions. This is the cause of the long term income inequality between males and females in the U.S. It is unjust to women and has a negative effect on real economic growth. Women have been catching up since the 1960s and that improves the performance of the U.S. economy. It will take decades, however, to full income equality between genders. There are no new defining parameters included in the model except the critical age, when people start to lose their incomes, was split into two critical ages for low-middle incomes and the highest incomes, which obey a power law distribution. Such an extension becomes necessary in order to match the observation that the female population in the earlier 1960s was practically not represented in the highest incomes.

Date: 2015-10
New Economics Papers: this item is included in nep-his
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Citations: View citations in EconPapers (2)

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Working Paper: Gender income disparity in the USA: analysis and dynamic modelling (2015)
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