IDEAS home Printed from https://ideas.repec.org/p/lis/liswps/305.html
   My bibliography  Save this paper

A Comparison of Parametric Models of Income Distribution across Countries and over Time

Author

Listed:
  • Ripsy Bandourian
  • Robert Turley
  • James McDonald

Abstract

The five-parameter generalized beta distribution and ten of its special cases are considered as models fore the size distribution of income. The models are fit to income data for 23 countries and various years - a total of 82 datasets. Of the models considered, the Weibull, Daagum and generalized beta of the second kind are best fitting of the models with two, three and four parameters for 62 percent, 84 percent, and 96 percent of the data sets, respectively. Increasing inequality with respect to pre-tax income is observed in most of the countries considered.

Suggested Citation

  • Ripsy Bandourian & Robert Turley & James McDonald, 2002. "A Comparison of Parametric Models of Income Distribution across Countries and over Time," LIS Working papers 305, LIS Cross-National Data Center in Luxembourg.
    • Handle: RePEc:lis:liswps:305
    as

    Download full text from publisher

    File URL: http://www.lisdatacenter.org/wps/liswps/305.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Salem, A B Z & Mount, T D, 1974. "A Convenient Descriptive Model of Income Distribution: The Gamma Density," Econometrica, Econometric Society, vol. 42(6), pages 1115-1127, November.
    2. Thurow, Lester C, 1970. "Analyzing the American Income Distribution," American Economic Review, American Economic Association, vol. 60(2), pages 261-269, May.
    3. McDonald, James B. & Xu, Yexiao J., 1995. "A generalization of the beta distribution with applications," Journal of Econometrics, Elsevier, vol. 69(2), pages 427-428, October.
    4. Singh, S K & Maddala, G S, 1976. "A Function for Size Distribution of Incomes," Econometrica, Econometric Society, vol. 44(5), pages 963-970, September.
    5. James B. McDonald, 2008. "Some Generalized Functions for the Size Distribution of Income," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 3, pages 37-55, Springer.
    6. Parker, Simon C, 1999. "The Beta as a Model for the Distribution of Earnings," Bulletin of Economic Research, Wiley Blackwell, vol. 51(3), pages 243-251, July.
    7. Sarabia, Jose Maria & Castillo, Enrique & Slottje, Daniel J., 2002. "Lorenz ordering between McDonald's generalized functions of the income size distribution," Economics Letters, Elsevier, vol. 75(2), pages 265-270, April.
    8. Parker, Simon C., 1999. "The generalised beta as a model for the distribution of earnings," Economics Letters, Elsevier, vol. 62(2), pages 197-200, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Samuel Dastrup & Rachel Hartshorn & James McDonald, 2007. "The impact of taxes and transfer payments on the distribution of income: A parametric comparison," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(3), pages 353-369, December.
    2. Vladimir Hlasny, 2021. "Parametric representation of the top of income distributions: Options, historical evidence, and model selection," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1217-1256, September.
    3. Michał Brzeziński, 2013. "Parametric Modelling of Income Distribution in Central and Eastern Europe," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 5(3), pages 207-230, September.
    4. Ripsy Bandourian, 2000. "Income Distributions: A Comparison across Countries and Time," LIS Working papers 231, LIS Cross-National Data Center in Luxembourg.
    5. José María Sarabia & Vanesa Jordá & Faustino Prieto & Montserrat Guillén, 2020. "Multivariate Classes of GB2 Distributions with Applications," Mathematics, MDPI, vol. 9(1), pages 1-21, December.
    6. Boccanfuso, Dorothée & Richard, Patrick & Savard, Luc, 2013. "Parametric and nonparametric income distribution estimators in CGE micro-simulation modeling," Economic Modelling, Elsevier, vol. 35(C), pages 892-899.
    7. Maxim Pinkovskiy & Xavier Sala-i-Martin, 2009. "Parametric Estimations of the World Distribution of Income," NBER Working Papers 15433, National Bureau of Economic Research, Inc.
    8. Kazuhiko Kakamu & Haruhisa Nishino, 2019. "Bayesian Estimation of Beta-type Distribution Parameters Based on Grouped Data," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 625-645, August.
    9. Jos'e Miguel Flores-Contr'o, 2024. "The Gerber-Shiu Expected Discounted Penalty Function: An Application to Poverty Trapping," Papers 2402.11715, arXiv.org, revised Sep 2024.
    10. Khosravi Tanak, A. & Mohtashami Borzadaran, G.R. & Ahmadi, J., 2015. "Entropy maximization under the constraints on the generalized Gini index and its application in modeling income distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 657-666.
    11. John Dagsvik & Zhiyang Jia & Bjørn Vatne & Weizhen Zhu, 2013. "Is the Pareto–Lévy law a good representation of income distributions?," Empirical Economics, Springer, vol. 44(2), pages 719-737, April.
    12. 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.
    13. Callealta Barroso, Francisco Javier & García-Pérez, Carmelo & Prieto-Alaiz, Mercedes, 2020. "Modelling income distribution using the log Student’s t distribution: New evidence for European Union countries," Economic Modelling, Elsevier, vol. 89(C), pages 512-522.
    14. Dorothée Boccanfuso & Bernard Decaluwé & Luc Savard, 2008. "Poverty, income distribution and CGE micro-simulation modeling: Does the functional form of distribution matter?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(2), pages 149-184, June.
    15. Sung Y. Park & Anil K. Bera, 2018. "Information theoretic approaches to income density estimation with an application to the U.S. income data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(4), pages 461-486, December.
    16. Duangkamon Chotikapanich & William E. Griffiths & Gholamreza Hajargasht & Wasana Karunarathne & D. S. Prasada Rao, 2018. "Using the GB2 Income Distribution," Econometrics, MDPI, vol. 6(2), pages 1-24, April.
    17. Feng Zhu, 2005. "A nonparametric analysis of the shape dynamics of the US personal income distribution: 1962-2000," BIS Working Papers 184, Bank for International Settlements.
    18. 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.
    19. Ramos, Arturo & Sanz-Gracia, Fernando, 2015. "US city size distribution revisited: Theory and empirical evidence," MPRA Paper 64051, University Library of Munich, Germany.
    20. Genya Kobayashi & Kazuhiko Kakamu, 2019. "Approximate Bayesian computation for Lorenz curves from grouped data," Computational Statistics, Springer, vol. 34(1), pages 253-279, March.

    More about this item

    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:lis:liswps:305. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Piotr Paradowski (email available below). General contact details of provider: https://edirc.repec.org/data/lisprlu.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.