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k-Generalized Statistics in Personal Income Distribution

Listed author(s):
  • F. Clementi
  • M. Gallegati
  • G. Kaniadakis

Starting from the generalized exponential function $\exp_{\kappa}(x)=(\sqrt{1+\kappa^{2}x^{2}}+\kappa x)^{1/\kappa}$, with $\exp_{0}(x)=\exp(x)$, proposed in Ref. [G. Kaniadakis, Physica A \textbf{296}, 405 (2001)], the survival function $P_{>}(x)=\exp_{\kappa}(-\beta x^{\alpha})$, where $x\in\mathbf{R}^{+}$, $\alpha,\beta>0$, and $\kappa\in[0,1)$, is considered in order to analyze the data on personal income distribution for Germany, Italy, and the United Kingdom. The above defined distribution is a continuous one-parameter deformation of the stretched exponential function $P_{>}^{0}(x)=\exp(-\beta x^{\alpha})$\textemdash to which reduces as $\kappa$ approaches zero\textemdash behaving in very different way in the $x\to0$ and $x\to\infty$ regions. Its bulk is very close to the stretched exponential one, whereas its tail decays following the power-law $P_{>}(x)\sim(2\beta\kappa)^{-1/\kappa}x^{-\alpha/\kappa}$. This makes the $\kappa$-generalized function particularly suitable to describe simultaneously the income distribution among both the richest part and the vast majority of the population, generally fitting different curves. An excellent agreement is found between our theoretical model and the observational data on personal income over their entire range.

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File URL: http://arxiv.org/pdf/physics/0607293
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Paper provided by arXiv.org in its series Papers with number physics/0607293.

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Date of creation: Jul 2006
Date of revision: Feb 2007
Publication status: Published in The European Physical Journal B, Vol: 57, Issue: 2, May II, 2007, pp: 187-193
Handle: RePEc:arx:papers:physics/0607293
Contact details of provider: Web page: http://arxiv.org/

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