IDEAS home Printed from https://ideas.repec.org/p/ecm/ausm04/213.html
   My bibliography  Save this paper

Estimating and Combining National Income Distributions using Limited Data

Author

Listed:
  • 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.

Suggested Citation

  • D.S. Prasada Rao & Duangkamon Chotikapanich & William E. Griffiths, 2004. "Estimating and Combining National Income Distributions using Limited Data," Econometric Society 2004 Australasian Meetings 213, Econometric Society.
  • Handle: RePEc:ecm:ausm04:213
    as

    Download full text from publisher

    File URL: http://repec.org/esAUSM04/up.10200.1077836480.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jordi Galí & Tommaso Monacelli, 2005. "Monetary Policy and Exchange Rate Volatility in a Small Open Economy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 707-734.
    2. Branko Milanovic, 2003. "The Ricardian Vice: Why Sala-i-Martin’s calculations of world income inequality are wrong," HEW 0305003, EconWPA.
    3. McDonald, James B, 1984. "Some Generalized Functions for the Size Distribution of Income," Econometrica, Econometric Society, vol. 52(3), pages 647-663, May.
    4. McDonald, James B & Ransom, Michael R, 1979. "Functional Forms, Estimation Techniques and the Distribution of Income," Econometrica, Econometric Society, vol. 47(6), pages 1513-1525, November.
    5. Chotikapanich, Duangkamon & Valenzuela, Rebecca & Rao, D S Prasada, 1997. "Global and Regional Inequality in the Distribution of Income: Estimation with Limited and Incomplete Data," Empirical Economics, Springer, vol. 22(4), pages 533-546.
    6. Xavier Sala-i-Martin, 2001. "The disturbing 'rise' of global income inequality," Economics Working Papers 616, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2002.
    7. Deininger, K & Squire, L, 1996. "Measuring Income Inequality : A New Data-Base," Papers 537, Harvard - Institute for International Development.
    8. McDonald, James B. & Xu, Yexiao J., 1995. "A generalization of the beta distribution with applications," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 133-152.
    9. Wilfling, Bernd, 1996. "Lorenz ordering of generalized beta-II income distributions," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 381-388.
    10. Quah, Danny, 2002. "One Third of the World's Growth and Inequality," WIDER Working Paper Series 038, World Institute for Development Economic Research (UNU-WIDER).
    11. Steve Dowrick & Muhammad Akmal, 2005. "Contradictory Trends In Global Income Inequality: A Tale Of Two Biases," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 51(2), pages 201-229, June.
    12. Quah, Danny, 2002. "One Third of the World's Growth and Inequality," CEPR Discussion Papers 3316, C.E.P.R. Discussion Papers.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Nicholas Rohde, 2008. "An alternative functional form for estimating the lorenz curve," Discussion Papers Series 384, School of Economics, University of Queensland, Australia.
    6. Rohde, Nicholas, 2009. "An alternative functional form for estimating the Lorenz curve," Economics Letters, Elsevier, vol. 105(1), pages 61-63, October.
    7. Gholamreza Hajargasht & William E. Griffiths, 2016. "Inference for Lorenz Curves," Department of Economics - Working Papers Series 2022, The University of Melbourne.
    8. 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.
    9. 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.
    10. Griffiths, William & Hajargasht, Gholamreza, 2015. "On GMM estimation of distributions from grouped data," Economics Letters, Elsevier, vol. 126(C), pages 122-126.
    11. 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.
    12. 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.
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. repec:eee:regeco:v:64:y:2017:i:c:p:148-161 is not listed on IDEAS
    18. 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.
    19. 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.
    20. 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.
    21. Gerencia de Riesgo Asobancaria - CIFIN, "undated". "Estimación de la Carga Financiera en Colombia," Temas de Estabilidad Financiera 056, Banco de la Republica de Colombia.
    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. 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.
    24. 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.
    25. repec:bla:revinw:v:63:y:2017:i:4:p:867-880 is not listed on IDEAS

    More about this item

    Keywords

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

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ecm:ausm04:213. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/essssea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.