IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v62y1999i2p197-200.html
   My bibliography  Save this article

The generalised beta as a model for the distribution of earnings

Author

Listed:
  • Parker, Simon C.

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecolet:v:62:y:1999:i:2:p:197-200
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165-1765(98)00213-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Thurow, Lester C, 1970. "Analyzing the American Income Distribution," American Economic Review, American Economic Association, vol. 60(2), pages 261-269, May.
    4. Solow, Robert M., 1979. "Another possible source of wage stickiness," Journal of Macroeconomics, Elsevier, vol. 1(1), pages 79-82.
    5. Singh, S K & Maddala, G S, 1976. "A Function for Size Distribution of Incomes," Econometrica, Econometric Society, vol. 44(5), pages 963-970, September.
    6. Sahota, Gian Singh, 1978. "Theories of Personal Income Distribution: A Survey," Journal of Economic Literature, American Economic Association, vol. 16(1), pages 1-55, March.
    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. 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.
    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. 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.
    5. Singh, Vijay P., 2018. "Systems of frequency distributions for water and environmental engineering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 50-74.
    6. 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.
    7. 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.
    8. James B. Mcdonald & Jeff Sorensen & Patrick A. Turley, 2013. "Skewness And Kurtosis Properties Of Income Distribution Models," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59(2), pages 360-374, June.
    9. 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.
    10. Christophe Muller, 2001. "The Properties of the Watts Poverty Index under Lognormality," Economics Bulletin, AccessEcon, vol. 9(1), pages 1-9.
    11. Markus Jäntti & Stephen Jenkins, 2010. "The impact of macroeconomic conditions on income inequality," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 8(2), pages 221-240, June.
    12. Vinh, Andrea & Griffiths, William E. & Chotikapanich, Duangkamon, 2010. "Bivariate income distributions for assessing inequality and poverty under dependent samples," Economic Modelling, Elsevier, vol. 27(6), pages 1473-1483, November.
    13. Vladimir Hlasny & Paolo Verme, 2022. "The Impact of Top Incomes Biases on the Measurement of Inequality in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 749-788, August.
    14. 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.
    15. 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.
    16. Jose Maria Sarabia & Francisco Azpitarte, 2012. "On the relationship between objective and subjective inequality indices and the natural rate of subjective inequality," Working Papers 248, ECINEQ, Society for the Study of Economic Inequality.
    17. Ripsy Bandourian, 2000. "Income Distributions: A Comparison across Countries and Time," LIS Working papers 231, LIS Cross-National Data Center in Luxembourg.
    18. Hu, Baiding, 1995. "A note on calculating the Gini index," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 353-358.
    19. Toda, Alexis Akira, 2012. "The double power law in income distribution: Explanations and evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 84(1), pages 364-381.
    20. Sarabia, J. -M. & Castillo, Enrique & Slottje, Daniel J., 1999. "An ordered family of Lorenz curves," Journal of Econometrics, Elsevier, vol. 91(1), pages 43-60, July.

    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:eee:ecolet:v:62:y:1999:i:2:p:197-200. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.