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Estimating Income Distributions Using a Mixture of Gamma Densities

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Author Info
Duangkamon Chotikapanich
William E Griffiths

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Abstract

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

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File URL: http://www.economics.unimelb.edu.au/SITE/research/workingpapers/wp08/1034.pdf
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Paper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 1034.

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Length: 27 pages
Date of creation: 2008
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Handle: RePEc:mlb:wpaper:1034

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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.:
  1. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January. [Downloadable!] (restricted)
  2. 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. [Downloadable!]
  3. Chotikapanich, Duangkamon & Griffiths, William E. & Rao, D. S. Prasada, 2007. "Estimating and Combining National Income Distributions Using Limited Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 97-109, January. [Downloadable!] (restricted)
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  4. 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. [Downloadable!]
  5. Hasegawa, Hikaru & Kozumi, Hideo, 2003. "Estimation of Lorenz curves: a Bayesian nonparametric approach," Journal of Econometrics, Elsevier, vol. 115(2), pages 277-291, August. [Downloadable!] (restricted)
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