IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1610.08918.html
   My bibliography  Save this paper

Income and wealth distribution of the richest Norwegian individuals: An inequality analysis

Author

Listed:
  • Maciej Jagielski
  • Kordian Czy.zewski
  • Ryszard Kutner
  • H. Eugene Stanley

Abstract

Using the empirical data from the Norwegian tax office, we analyse the wealth and income of the richest individuals in Norway during the period 2010--2013. We find that both annual income and wealth level of the richest individuals are describable using the Pareto law. We find that the robust mean Pareto exponent over the four-year period to be $\approx 2.3$ for income and $\approx 1.5$ for wealth.

Suggested Citation

  • Maciej Jagielski & Kordian Czy.zewski & Ryszard Kutner & H. Eugene Stanley, 2016. "Income and wealth distribution of the richest Norwegian individuals: An inequality analysis," Papers 1610.08918, arXiv.org.
    • Handle: RePEc:arx:papers:1610.08918
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1610.08918
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kyungsik Kim & Seong-Min Yoon, 2004. "Power Law Distributions in Korean Household Incomes," Papers cond-mat/0403161, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fabio Clementi & Mauro Gallegati, 2005. "Pareto's Law of Income Distribution: Evidence for Grermany, the United Kingdom, and the United States," Microeconomics 0505006, University Library of Munich, Germany.
    2. Jagielski, Maciej & Czyżewski, Kordian & Kutner, Ryszard & Stanley, H. Eugene, 2017. "Income and wealth distribution of the richest Norwegian individuals: An inequality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 330-333.

    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:1610.08918. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.