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Using the GB2 Income Distribution

Author

Listed:
  • Duangkamon Chotikapanich

    (Monash Business School, Monash University, Melbourne VIC 3145, Australia)

  • William E. Griffiths

    (Department of Economics, University of Melbourne, Melbourne VIC 3010, Australia)

  • Gholamreza Hajargasht

    (Department of Accounting, Economics and Finance, Swinburne University of Technology, Hawthorn VIC 3122, Australia)

  • Wasana Karunarathne

    (Department of Economics, University of Melbourne, Melbourne VIC 3010, Australia)

  • D. S. Prasada Rao

    (School of Economics, University of Queensland, St. Lucia QLD 4072, Australia)

Abstract

To use the generalized beta distribution of the second kind (GB2) for the analysis of income and other positively skewed distributions, knowledge of estimation methods and the ability to compute quantities of interest from the estimated parameters are required. We review estimation methodology that has appeared in the literature, and summarize expressions for inequality, poverty, and pro-poor growth that can be used to compute these measures from GB2 parameter estimates. An application to data from China and Indonesia is provided.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jecnmx:v:6:y:2018:i:2:p:21-:d:141682
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    References listed on IDEAS

    as
    1. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
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    3. 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.
    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. Stephen P. Jenkins, 2009. "Distributionally‐Sensitive Inequality Indices And The Gb2 Income Distribution," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(2), pages 392-398, June.
    6. 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.
    7. Claudio Quintano & Antonella D'Agostino, 2006. "Studying Inequality In Income Distribution Of Single‐Person Households In Four Developed Countries," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 52(4), pages 525-546, December.
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    24. 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.
    25. 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.
    26. Sarabia, José María & Jordá, Vanesa, 2014. "Explicit expressions of the Pietra index for the generalized function for the size distribution of income," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 582-595.
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    Cited by:

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    2. Mathias Silva, 2023. "Parametric estimation of income distributions using grouped data: an Approximate Bayesian Computation approach [Working Papers / Documents de travail]," Working Papers hal-04066544, HAL.
    3. 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.
    4. Masato Okamoto, 2022. "Lorenz and Polarization Orderings of the Double-Pareto Lognormal Distribution and Other Size Distributions," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 548-574, November.
    5. Vanesa Jorda & José María Sarabia & Markus Jäntti, 2021. "Inequality measurement with grouped data: Parametric and non‐parametric methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 964-984, July.
    6. Walter Bossert & Conchita D’Ambrosio & Kohei Kamaga, 2021. "Extreme Values, Means, and Inequality Measurement," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(3), pages 564-590, September.
    7. Vanesa Jorda & José María Sarabia & Markus Jäntti, 2020. "Estimation of Income Inequality from Grouped Data," LIS Working papers 804, LIS Cross-National Data Center in Luxembourg.
    8. Jiong Liu & R. A. Serota, 2023. "Rethinking Generalized Beta family of distributions," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(2), pages 1-14, February.
    9. Mathias Silva, 2023. "Parametric models of income distributions integrating misreporting and non-response mechanisms," AMSE Working Papers 2311, Aix-Marseille School of Economics, France.
    10. Jordá, Vanesa & Niño-Zarazúa, Miguel, 2019. "Global inequality: How large is the effect of top incomes?," World Development, Elsevier, vol. 123(C), pages 1-1.
    11. Jiong Liu & R. A. Serota, 2022. "Rethinking Generalized Beta Family of Distributions," Papers 2209.05225, arXiv.org.
    12. 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.
    13. Dashti Moghaddam, M. & Mills, Jeffrey & Serota, R.A., 2020. "From a stochastic model of economic exchange to measures of inequality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    14. Amparo Ba'illo & Javier C'arcamo & Carlos Mora-Corral, 2021. "Extremal points of Lorenz curves and applications to inequality analysis," Papers 2103.03286, arXiv.org.
    15. William Griffiths & Duangkamon Chotikapanich & Gholamreza Hajargasht, 2021. "A Note on Inequality Measures for Mixtures of Double Pareto-Lognormal Distributions," Monash Econometrics and Business Statistics Working Papers 14/21, Monash University, Department of Econometrics and Business Statistics.
    16. Kyohei Shibano & Gento Mogi, 2020. "Electricity Consumption Forecast Model Using Household Income: Case Study in Tanzania," Energies, MDPI, vol. 13(10), pages 1-14, May.

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