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Estimating and Combining National Income Distributions using Limited Data

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  • D.S. Prasada Rao
  • Duangkamon Chotikapanich
  • William E. Griffiths

Abstract

Recently, there has been a resurgence of studies on the distribution of income and inequality at regional and global levels, largely driven by the concerns of economists, international development organisations and the general public about the overall effects of globalisation on growth and inequality. A major data problem encountered in these studies is the nature of income distribution data that are available mainly in a summary form that includes mean (average) income and income shares of quintile or decile groups of the population. Past studies have either ignored distributional characteristics within each population sub-group, implying that all individuals in a quintile or decile group have the same income, or used simple distributions like the lognormal or Pareto to model income distribution within each country. The aim of the paper is to estimate national and regional income distributions within a more general framework that relaxes the assumption of constant-income-within-groups and is based on a general and versatile class of income distributions. A technique to estimate parameters of a class of generalised Beta distributions using grouped data is proposed. Regional income distribution is modelled using a mixture of country-specific distributions and its properties are examined. The techniques are used to analyse national and regional inequality trends for eight East Asian countries and three benchmark years 1988, 1993 and 2000.

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Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society 2004 Australasian Meetings with number 213.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:ausm04:213

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Keywords: Income Distribution; Generalized Beta; Mixture of Distributions; Inequality;

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Cited by:
  1. Shorrocks, Anthony & Wan, Guanghua, 2008. "Ungrouping Income Distributions: Synthesising Samples for Inequality and Poverty Analysis," Working Paper Series RP2008/16, World Institute for Development Economic Research (UNU-WIDER).
  2. Chakravarty, Shoibal & Tavoni, Massimo, 2013. "Energy poverty alleviation and climate change mitigation: Is there a trade off?," Energy Economics, Elsevier, vol. 40(S1), pages S67-S73.
  3. Gholamreza Hajargsht & William E. Griffiths & Joseph Brice & D.S. Prasada Rao & Duangkamon Chotikapanich, 2011. "GMM Estimation of Income Distributions from Grouped Data," Department of Economics - Working Papers Series 1129, The University of Melbourne.
  4. Duangkamon Chotikapanich & D. S. Prasada Rao & Kam Ki Tang, 2007. "Estimating Income Inequality In China Using Grouped Data And The Generalized Beta Distribution," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 53(1), pages 127-147, 03.
  5. Shoibal Chakravarty & Massimo Tavoni, 2013. "Energy Poverty Alleviation and Climate Change Mitigation: is There a Trade off?," Working Papers 2013.25, Fondazione Eni Enrico Mattei.
  6. Gerencia de Riesgo Asobancaria - CIFIN, . "Estimación de la Carga Financiera en Colombia," Temas de Estabilidad Financiera 056, Banco de la Republica de Colombia.
  7. Duangkamon Chotikapanich & William Griffiths & Wasana Karunarathne & D.S. Prasada Rao, 2013. "Calculating Poverty Measures from the Generalised Beta Income Distribution," The Economic Record, The Economic Society of Australia, vol. 89, pages 48-66, 06.
  8. Lee, Jongchul, 2013. "A provincial perspective on income inequality in urban China and the role of property and business income," China Economic Review, Elsevier, vol. 26(C), pages 140-150.
  9. Duangkamon Chotikapanich & William E Griffiths & D.S. Prasada Rao & Vicar Valencia, 2009. "Global Income Distribution and Inequality: 1993 and 2000," Department of Economics - Working Papers Series 1062, The University of Melbourne.
  10. David Warner & Prasada Rao & William E. Griffiths & Duangkamon Chotikapanich, 2011. "Global Inequality: Levels and Trends, 1993-2005," Discussion Papers Series 436, School of Economics, University of Queensland, Australia.
  11. Chotikapanich, Duangkamon & Griffiths, William E. & Rao, D.S. Prasada & Karunarathne, Wasana, 2014. "Income Distributions, Inequality, and Poverty in Asia, 1992–2010," ADBI Working Papers 468, Asian Development Bank Institute.
  12. Duangkamon Chotikapanich & William E Griffiths, 2008. "Estimating Income Distributions Using a Mixture of Gamma Densities," Department of Economics - Working Papers Series 1034, The University of Melbourne.
  13. Pinkovskiy, Maxim L., 2014. "World welfare is rising: estimation using nonparametric bounds on welfare measures," Staff Reports 662, Federal Reserve Bank of New York.
  14. Nicholas Rohde, 2008. "An alternative functional form for estimating the lorenz curve," Discussion Papers Series 384, School of Economics, University of Queensland, Australia.
  15. Rohde, Nicholas, 2009. "An alternative functional form for estimating the Lorenz curve," Economics Letters, Elsevier, vol. 105(1), pages 61-63, October.
  16. William E. Griffiths and Gholamreza Hajargasht, 2012. "GMM Estimation of Mixtures from Grouped Data:," Department of Economics - Working Papers Series 1148, The University of Melbourne.
  17. Gholamreza Hajargsht, William E. Griffiths, Joseph Brice, D.S. Prasada Rao, Duangkamon Chotikapanich, 2012. "Inference for Income Distributions Using Grouped Data," Department of Economics - Working Papers Series 1140, The University of Melbourne.

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