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Global Income Distributions and Inequality, 1993 and 2000: Incorporating Country-Level Inequality Modeled with Beta Distributions

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Author Info

  • Duangkamon Chotikapanich

    (Monash University)

  • William E. Griffiths

    (University of Melbourne)

  • D. S. Prasada Rao

    (University of Queensland)

  • Vicar Valencia

    (Rochester Institute of Technology)

Abstract

Using a method-of-moments estimator, flexible three-parameter beta distributions are fitted to aggregate country-level income data to overcome an untenable assumption of previous studies that persons within each income group receive the same income. Regional and global income distributions are derived as weighted mixtures of country-specific distributions. Analytical expressions for Gini and Theil's measures of inequality at country, regional, and global levels are derived in terms of the parameters of the beta distributions. Application to data for 91 countries in 1993 and 2000 reveals a high degree of global inequality, with evidence of declining inequality, largely attributable to growth in China. © 2011 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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Bibliographic Info

Article provided by MIT Press in its journal Review of Economics and Statistics.

Volume (Year): 94 (2012)
Issue (Month): 1 (February)
Pages: 52-73

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Handle: RePEc:tpr:restat:v:94:y:2012:i:1:p:52-73

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Web page: http://mitpress.mit.edu/journals/

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Cited by:
  1. Andreas Chai & Wolfhard Kaus, 2013. "Signalling to whom? Conspicuous spending and the local density of the social group income distribution," Papers on Economics and Evolution 2012-18, Max Planck Institute of Economics, Evolutionary Economics Group.
  2. Duangkamon Chotikapanich, William Griffiths, Wasana Karunarathne, D.S. Prasada Rao, 2012. "Calculating Poverty Measures from the Generalized Beta Income Distribution," Department of Economics - Working Papers Series 1154, The University of Melbourne.
  3. 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.
  4. Hajargasht, Gholamreza & Griffiths, William E., 2013. "Pareto–lognormal distributions: Inequality, poverty, and estimation from grouped income data," Economic Modelling, Elsevier, vol. 33(C), pages 593-604.
  5. Niklas Potrafke, 2014. "The Evidence on Globalization," CESifo Working Paper Series 4708, CESifo Group Munich.
  6. 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.

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