IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1207.6081.html
   My bibliography  Save this paper

Exploiting the flexibility of a family of models for taxation and redistribution

Author

Listed:
  • Maria Letizia Bertotti
  • Giovanni Modanese

Abstract

We discuss a family of models expressed by nonlinear differential equation systems describing closed market societies in the presence of taxation and redistribution. We focus in particular on three example models obtained in correspondence to different parameter choices. We analyse the influence of the various choices on the long time shape of the income distribution. Several simulations suggest that behavioral heterogeneity among the individuals plays a definite role in the formation of fat tails of the asymptotic stationary distributions. This is in agreement with results found with different approaches and techniques. We also show that an excellent fit for the computational outputs of our models is provided by the k-generalized distribution introduced by G. Kaniadakis (Physica A 296 (2001) 405-425).

Suggested Citation

  • Maria Letizia Bertotti & Giovanni Modanese, 2012. "Exploiting the flexibility of a family of models for taxation and redistribution," Papers 1207.6081, arXiv.org, revised Mar 2014.
  • Handle: RePEc:arx:papers:1207.6081
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1207.6081
    File Function: Latest version
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maria Letizia Bertotti & Giovanni Modanese, 2014. "Micro to macro models for income distribution in the absence and in the presence of tax evasion," Papers 1403.0015, arXiv.org.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:1207.6081. 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.