Relationship between normal and excessive personal income differentiation and regional economic performance indicators

M. Yu. Malkina ()
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M. Yu. Malkina: Nizhny Novgorod State University

Regional Research of Russia, 2017, vol. 7, issue 2, 153-161

Abstract: Abstract The paper uses A.Yu. Shevyakov’s approach to the decomposition of the Gini coefficient into normal and excessive inequalities, the full deflation method for determining real income and real labor productivity, correlation and regression analysis, and the construction of Cobb–Douglas production functions. Three differentiation levels of normal and excessive inequalities (poverty line, social minimum line, and social well-being line) are proposed. For Russian regions in 2013, the study has found an inverse relationship between real per capita income and the Gini coefficient of excessive inequality, as well as a direct relationship between real per capita income and the Gini coefficient of normal inequality, except for the three most affluent regions, which show a reverse trend of decline in normal inequality. Correlations of normal and excessive inequalities with general development indicators, composition and dynamics of the population, the structure of income and gross regional product, sectoral structure of the economy, and the population’s wealth are revealed. A positive correlation for normal inequality and a negative correlation for excessive inequality with real output in Russian regions are confirmed based on the inclusion of Gini coefficients in the five-factor interregional Cobb–Douglas production function. It is concluded that excessive inequality, on the one hand, is a consequence of the low development level and, on the other hand, suppresses production possibilities and incentives. Normal inequality promotes economic development, which is first accompanied by a growth in normal inequality, followed by a decline.

Keywords: region; household income; Gini coefficient; normal and excessive inequality; development indicators; Cobb–Douglas function (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1134/S2079970517020058

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