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Calculating Poverty Measures from the Generalised Beta Income Distribution

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  • Duangkamon Chotikapanich
  • William Griffiths
  • Wasana Karunarathne
  • D.S. Prasada Rao

Abstract

Data for measuring poverty and income inequality are frequently available in a summary form that describes the proportion of income or expenditure for each of a number of population proportions. While various discrete measures can be applied directly to data in this limited form, these discrete measures typically ignore inequality within each group. This problem can be overcome by fitting a parametric income distribution to the grouped data and computing required quantities from the estimated parameters of this distribution. In this paper we show how to calculate several poverty measures from parameters of the generalized beta distribution of the second kind, and its popular special cases. An analysis of poverty changes in ten countries from South and Southeast Asia is used to illustrate the methodology.

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Bibliographic Info

Article provided by The Economic Society of Australia in its journal The Economic Record.

Volume (Year): 89 (2013)
Issue (Month): (06)
Pages: 48-66

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Handle: RePEc:bla:ecorec:v:89:y:2013:i::p:48-66

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References

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  1. Gholamreza Hajargasht & William E. Griffiths & Joseph Brice & D.S. Prasada Rao & Duangkamon Chotikapanich, 2012. "Inference for Income Distributions Using Grouped Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 563-575, May.
  2. Madden, David, 2000. "Relative or Absolute Poverty Lines: A New Approach," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 46(2), pages 181-99, June.
  3. Lars Osberg & Kuan Xu, 2008. "How Should We Measure Poverty in a Changing World? Methodological Issues and Chinese Case Study," Review of Development Economics, Wiley Blackwell, vol. 12(2), pages 419-441, 05.
  4. Ravallion, Martin & Chen, Shaohua & Sangraula, Prem, 2008. "Dollar a day revisited," Policy Research Working Paper Series 4620, The World Bank.
  5. McDonald, James B, 1984. "Some Generalized Functions for the Size Distribution of Income," Econometrica, Econometric Society, vol. 52(3), pages 647-63, May.
  6. Duangkamon Chotikapanich & William E. Griffiths & D. S. Prasada Rao & Vicar Valencia, 2012. "Global Income Distributions and Inequality, 1993 and 2000: Incorporating Country-Level Inequality Modeled with Beta Distributions," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 52-73, February.
  7. Duangkamon Chotikapanich & William E. Griffiths & D.S. Prasada Rao, 2005. "Estimating and Combining National Income Distributions using Limited Data," Department of Economics - Working Papers Series 926, The University of Melbourne.
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Cited by:
  1. Michał Brzeziński, 2013. "Parametric Modelling of Income Distribution in Central and Eastern Europe," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 5(3), pages 207-230, September.
  2. 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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