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Estimating and Combining National Income Distributions Using Limited Data

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

Abstract

A major problem encountered in studies of income inequality at regional and global levels is the estimation of income distributions from data that are in a summary form. In this paper we estimate national and regional income distributions within a general framework that relaxes the assumption of constant income within groups. A technique to estimate the parameters of a beta-2 distribution 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 two benchmark years, 1988 and 1993.
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Suggested Citation

  • 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.
  • Handle: RePEc:bes:jnlbes:v:25:y:2007:p:97-109
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    Citations

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    Cited by:

    1. Griffiths, William & Hajargasht, Gholamreza, 2015. "On GMM estimation of distributions from grouped data," Economics Letters, Elsevier, vol. 126(C), pages 122-126.
    2. 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.
    3. David Warner & D. S. Prasada Rao & William E. Griffiths & Duangkamon Chotikapanich, 2014. "Global Inequality; Levels and Trends, 1993–2005: How Sensitive are These to the Choice of PPPs and Real Income Measures?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S2), pages 281-304, November.
    4. Pinkovskiy, Maxim L., 2013. "World welfare is rising: Estimation using nonparametric bounds on welfare measures," Journal of Public Economics, Elsevier, vol. 97(C), pages 176-195.
    5. 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.
    6. repec:eee:regeco:v:64:y:2017:i:c:p:148-161 is not listed on IDEAS
    7. 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.
    8. 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, June.
    9. Camelia Minoiu & Sanjay Reddy, 2014. "Kernel density estimation on grouped data: the case of poverty assessment," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(2), pages 163-189, June.
    10. Thomas Mayrhofer & Hendrik Schmitz, 2014. "Testing the relationship between income inequality and life expectancy: a simple correction for the aggregation effect when using aggregated data," Journal of Population Economics, Springer;European Society for Population Economics, vol. 27(3), pages 841-856, July.
    11. Jin, Hailong & Qian, Hang & Wang, Tong & Choi, E. Kwan, 2014. "Income distribution in urban China: An overlooked data inconsistency issue," China Economic Review, Elsevier, vol. 30(C), pages 383-396.
    12. repec:bla:revinw:v:63:y:2017:i:4:p:867-880 is not listed on IDEAS
    13. Shorrocks, Anthony & Wan, Guanghua, 2008. "Ungrouping Income Distributions: Synthesising Samples for Inequality and Poverty Analysis," WIDER Working Paper Series 016, World Institute for Development Economic Research (UNU-WIDER).
    14. 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, March.
    15. 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.
    16. 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.
    17. 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.
    18. Gerencia de Riesgo Asobancaria - CIFIN, "undated". "Estimación de la Carga Financiera en Colombia," Temas de Estabilidad Financiera 056, Banco de la Republica de Colombia.
    19. Nicholas Rohde, 2008. "An alternative functional form for estimating the lorenz curve," Discussion Papers Series 384, School of Economics, University of Queensland, Australia.
    20. Rohde, Nicholas, 2009. "An alternative functional form for estimating the Lorenz curve," Economics Letters, Elsevier, vol. 105(1), pages 61-63, October.
    21. 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.
    22. Chakravarty, Shoibal & Tavoni, Massimo, 2013. "Energy poverty alleviation and climate change mitigation: Is there a trade off?," Energy Economics, Elsevier, vol. 40(S1), pages 67-73.
    23. Gholamreza Hajargasht & William E. Griffiths, 2016. "Inference for Lorenz Curves," Department of Economics - Working Papers Series 2022, The University of Melbourne.
    24. 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.
    25. Richard Bluhm & Denis de Crombrugghe & Adam Szirmai, 2016. "Poverty Accounting. A fractional response approach to poverty decomposition," Working Papers 413, ECINEQ, Society for the Study of Economic Inequality.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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