IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Estimating Income Distributions Using a Mixture of Gamma Densities

  • Duangkamon Chotikapanich
  • William E Griffiths

The estimation of income distributions is important for assessing income inequality and poverty and for making comparisons of inequality and poverty over time, countries and regions, as well as before and after changes in taxation and transfer policies. Distributions have been estimated both parametrically and nonparametrically. Parametric estimation is convenient because it facilitates subsequent inferences about inequality and poverty measures and lends itself to further analysis such as the combining of regional distributions into a national distribution. Nonparametric estimation makes inferences more difficult, but it does not place what are sometimes unreasonable restrictions on the nature of the distribution. By estimating a mixture of gamma distributions, in this paper we attempt to benefit from the advantages of parametric estimation without suffering the disadvantage of inflexibility. Using a sample of Canadian income data, we use Bayesian inference to estimate gamma mixtures with two and three components. We describe how to obtain a predictive density and distribution function for income and illustrate the flexibility of the mixture. Posterior densities for Lorenz curve ordinates and the Gini coefficient are obtained

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.economics.unimelb.edu.au/downloads/wpapers-08/1034.pdf
Our checks indicate that this address may not be valid because: 404 Not Found (http://www.economics.unimelb.edu.au/downloads/wpapers-08/1034.pdf [301 Moved Permanently]--> http://fbe.unimelb.edu.au/economics/downloads/wpapers-08/1034.pdf). If this is indeed the case, please notify (Aminata Doumbia)


Download Restriction: no

Paper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 1034.

as
in new window

Length: 27 pages
Date of creation: 2008
Date of revision:
Handle: RePEc:mlb:wpaper:1034
Contact details of provider: Postal: Department of Economics, The University of Melbourne, 4th Floor, FBE Building, Level 4, 111 Barry Street. Victoria, 3010, Australia
Phone: +61 3 8344 5355
Fax: +61 3 8344 6899
Web page: http://www.economics.unimelb.edu.auEmail:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. D.S. Prasada Rao & Duangkamon Chotikapanich & William E. Griffiths, 2004. "Estimating and Combining National Income Distributions using Limited Data," Econometric Society 2004 Australasian Meetings 213, Econometric Society.
  2. Duangkamon Chotikapanich & William E. Griffiths, 2006. "Bayesian Assessment of Lorenz and Stochastic Dominance in Income Distributions," Department of Economics - Working Papers Series 960, The University of Melbourne.
  3. Frank A Cowell, 1996. "Estimation of Inequality Indices," STICERD - Distributional Analysis Research Programme Papers 25, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  4. Hasegawa, Hikaru & Kozumi, Hideo, 2003. "Estimation of Lorenz curves: a Bayesian nonparametric approach," Journal of Econometrics, Elsevier, vol. 115(2), pages 277-291, August.
  5. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:mlb:wpaper:1034. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Aminata Doumbia)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.