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$\kappa$-generalized models of income and wealth distributions: A survey

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  • F. Clementi
  • M. Gallegati
  • G. Kaniadakis
  • S. Landini

Abstract

The paper provides a survey of results related to the "$\kappa$-generalized distribution", a statistical model for the size distribution of income and wealth. Topics include, among others, discussion of basic analytical properties, interrelations with other statistical distributions as well as aspects that are of special interest in the income distribution field, such as the Gini index and the Lorenz curve. An extension of the basic model that is most able to accommodate the special features of wealth data is also reviewed. The survey of empirical applications given in this paper shows the $\kappa$-generalized models of income and wealth to be in excellent agreement with the observed data in many cases.

Suggested Citation

  • F. Clementi & M. Gallegati & G. Kaniadakis & S. Landini, 2016. "$\kappa$-generalized models of income and wealth distributions: A survey," Papers 1610.08676, arXiv.org.
    • Handle: RePEc:arx:papers:1610.08676
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    References listed on IDEAS

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    1. Cowell, Frank, 2011. "Measuring Inequality," OUP Catalogue, Oxford University Press, edition 3, number 9780199594047, Decembrie.
    2. Masato Okamoto, 2013. "Extension of the κ-generalized distribution: new four-parameter models for the size distribution of income and consumption," LIS Working papers 600, LIS Cross-National Data Center in Luxembourg.
    3. Atkinson, Anthony B., 2015. "Inequality: what can be done?," LSE Research Online Documents on Economics 101810, London School of Economics and Political Science, LSE Library.
    4. P. Jenkins, Stephen & Jäntti, Markus, 2005. "Methods for summarizing and comparing wealth distributions," ISER Working Paper Series 2005-05, Institute for Social and Economic Research.
    5. Chakrabarti,Bikas K. & Chakraborti,Anirban & Chakravarty,Satya R. & Chatterjee,Arnab, 2013. "Econophysics of Income and Wealth Distributions," Cambridge Books, Cambridge University Press, number 9781107013445, December.
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    Cited by:

    1. Kazuhiko Kakamu & Haruhisa Nishino, 2019. "Bayesian Estimation of Beta-type Distribution Parameters Based on Grouped Data," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 625-645, August.
    2. Fabio Clementi & Mauro Gallegati & Lisa Gianmoena & Simone Landini & Joseph E. Stiglitz, 2019. "Mis-measurement of inequality: a critical reflection and new insights," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 891-921, December.
    3. Yuri Biondi & Simone Righi, 2019. "Inequality, mobility and the financial accumulation process: a computational economic analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 93-119, March.

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