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This paper proposes a statistical mechanics approach to the analysis ofincome distribution and inequality. A new distribution function, having itsroots in the framework of k-generalized statistics, is derived that isparticularly suitable to describe the whole spectrum of incomes, from thelow-middle income region up to the high-income Pareto power-law regime.Analytical expressions for the shape, moments and some other basic statisticalproperties are given. Furthermore, several well-known econometric tools formeasuring inequality, which all exist in a closed form, are considered. Amethod for parameter estimation is also discussed. The model is shown to fitremarkably well the data on personal income for the United States, and theanalysis of inequality performed in terms of its parameters reveals verypowerful.

A k-generalized statistical mechanics approach to income analysis