IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2506.20881.html
   My bibliography  Save this paper

Modeling Income Distribution with the Gause-Witt Population Ecology System

Author

Listed:
  • Marcelo B. Ribeiro

Abstract

This paper presents an empirical application of the Gause-Witt model of population ecology and ecosystems to the income distribution competitive dynamics of social classes in economic systems. The Gause-Witt mathematical system of coupled nonlinear first-order ordinary differential equations employed to model population of species sharing the same ecological niche and competing for the same resources was applied to the income data of Brazil. Previous studies using Brazilian income data from 1981 to 2009 showed that the complementary cumulative distribution functions built from yearly datasets have two distinct segments: the lower income region comprising of about 99% of the population can be represented by the Gompertz curve, whereas the richest 1% is described by the Pareto power-law. The results of applying the Gause-Witt system to Brazilian income data in order to describe the distributive competition dynamics of these two population shares indicate that the 99% and 1% income classes are mostly in the dynamic state of stable coexistence.

Suggested Citation

  • Marcelo B. Ribeiro, 2025. "Modeling Income Distribution with the Gause-Witt Population Ecology System," Papers 2506.20881, arXiv.org.
  • Handle: RePEc:arx:papers:2506.20881
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2506.20881
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2506.20881. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.