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Tsallis statistics in the income distribution of Brazil

Author

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  • Abner D. Soares

    (Comiss\~ao Nacional de Energia Nuclear - CNEN, Rio de Janeiro)

  • Newton J. Moura Jr.

    (Instituto Brasileiro de Geografia e Estat\'istica - IBGE, Rio de Janeiro)

  • Marcelo B. Ribeiro

    (Instituto de F\'isica, Universidade Federal do Rio de Janeiro - UFRJ
    Observat\'orio do Valongo, Universidade Federal do Rio de Janeiro - UFRJ)

Abstract

This paper discusses the empirical evidence of Tsallis statistical functions in the personal income distribution of Brazil. Yearly samples from 1978 to 2014 were linearized by the q-logarithm and straight lines were fitted to the entire range of the income data in all samples, producing a two-parameters-only single function representation of the whole distribution in every year. The results showed that the time evolution of the parameters is periodic and plotting one in terms of the other reveals a cycle mostly clockwise. It was also found that the empirical data oscillate periodically around the fitted straight lines with the amplitude growing as the income values increase. Since the entire income data range can be fitted by a single function, this raises questions on previous results claiming that the income distribution is constituted by a well defined two-classes-base income structure, since such a division in two very distinct income classes might not be an intrinsic property of societies, but a consequence of an a priori fitting-choice procedure that may leave aside possibly important income dynamics at the intermediate levels.

Suggested Citation

  • Abner D. Soares & Newton J. Moura Jr. & Marcelo B. Ribeiro, 2016. "Tsallis statistics in the income distribution of Brazil," Papers 1602.06855, arXiv.org, revised Mar 2016.
    • Handle: RePEc:arx:papers:1602.06855
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    Cited by:

    1. da Silva, Sérgio Luiz Eduardo Ferreira, 2021. "Newton’s cooling law in generalised statistical mechanics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    2. Răzvan-Cornel Sfetcu & Vasile Preda, 2024. "Order Properties Concerning Tsallis Residual Entropy," Mathematics, MDPI, vol. 12(3), pages 1-16, January.
    3. Duarte Queirós, Sílvio M. & Anteneodo, Celia, 2016. "Complexity in quantitative finance and economics," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 1-2.
    4. Néda, Zoltán & Gere, István & Biró, Tamás S. & Tóth, Géza & Derzsy, Noemi, 2020. "Scaling in income inequalities and its dynamical origin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    5. Martins, Adriel M.F. & Fernandes, Leonardo H.S. & Nascimento, Abraão D.C., 2023. "Scientific progress in information theory quantifiers," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    6. Paulo L. dos Santos & Jangho Yang, 2019. "The persistent and informative distribution of returns on capital," Economics and Business Letters, Oviedo University Press, vol. 8(3), pages 156-165.
    7. Răzvan-Cornel Sfetcu & Sorina-Cezarina Sfetcu & Vasile Preda, 2021. "Ordering Awad–Varma Entropy and Applications to Some Stochastic Models," Mathematics, MDPI, vol. 9(3), pages 1-15, January.
    8. Paulo L. dos Santos, 2017. "The Principle of Social Scaling," Complexity, Hindawi, vol. 2017, pages 1-9, December.

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