IDEAS home Printed from https://ideas.repec.org/h/spr/esichp/978-0-387-72796-7_8.html
   My bibliography  Save this book chapter

The Generalized Beta Distribution as a Model for the Distribution of Income: Estimation of Related Measures of Inequality

In: Modeling Income Distributions and Lorenz Curves

Author

Listed:
  • James B. McDonald

    (Brigham Young University)

  • Michael Ransom

    (Brigham Young University)

Abstract

The generalized beta (GB) is considered as a model for the distribution of income. It is well known that its special cases include Dagum’s distribution along with the Singh-Maddala distribution. Related measures of inequality such as the Gini Coefficient, Pietra Index, or Theil Index are expressed in terms of the parameters of the generalized beta. This paper also explores the use of numerical integration techniques for calculating inequality indexes. Numerical integration may be useful since in some cases it may be computationally very difficult to evaluate the equations that have been derived or the equations are not available. We provide examples from the distribution of family income in the United States for the year 2000.

Suggested Citation

  • James B. McDonald & Michael Ransom, 2008. "The Generalized Beta Distribution as a Model for the Distribution of Income: Estimation of Related Measures of Inequality," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 8, pages 147-166, Springer.
    • Handle: RePEc:spr:esichp:978-0-387-72796-7_8
    DOI: 10.1007/978-0-387-72796-7_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:esichp:978-0-387-72796-7_8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.