IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp2831.html
   My bibliography  Save this paper

Inequality and the GB2 Income Distribution

Author

Listed:
  • Jenkins, Stephen P.

    (London School of Economics)

Abstract

The generalized entropy class of inequality indices is derived for Generalized Beta of the Second Kind (GB2) income distributions, thereby providing a full range of top-sensitive and bottom-sensitive measures. An examination of British income inequality in 1994/95 and 2004/05 illustrates the analysis.

Suggested Citation

  • Jenkins, Stephen P., 2007. "Inequality and the GB2 Income Distribution," IZA Discussion Papers 2831, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp2831
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp2831.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Frank A. Cowell, 1980. "On the Structure of Additive Inequality Measures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(3), pages 521-531.
    2. Shorrocks, Anthony F, 1984. "Inequality Decomposition by Population Subgroups," Econometrica, Econometric Society, vol. 52(6), pages 1369-1385, November.
    3. Cowell, Frank A. & Flachaire, Emmanuel, 2007. "Income distribution and inequality measurement: The problem of extreme values," Journal of Econometrics, Elsevier, vol. 141(2), pages 1044-1072, December.
    4. Stephen P. Jenkins, 2007. "GB2FIT: Stata module to fit Generalized Beta of the Second Kind distribution by maximum likelihood," Statistical Software Components S456823, Boston College Department of Economics, revised 17 Jul 2012.
    5. Frank A. Cowell, 2008. "Income Distribution and Inequality," Chapters, in: John B. Davis & Wilfred Dolfsma (ed.), The Elgar Companion to Social Economics, chapter 13, Edward Elgar Publishing.
    6. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
    7. 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.
    8. Butler, Richard J. & McDonald, James B., 1989. "Using incomplete moments to measure inequality," Journal of Econometrics, Elsevier, vol. 42(1), pages 109-119, September.
    9. Feng, Shuaizhang & Burkhauser, Richard V. & Butler, J.S., 2006. "Levels and Long-Term Trends in Earnings Inequality: Overcoming Current Population Survey Censoring Problems Using the GB2 Distribution," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 57-62, January.
    10. 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.
    11. Bourguignon, Francois, 1979. "Decomposable Income Inequality Measures," Econometrica, Econometric Society, vol. 47(4), pages 901-920, July.
    12. 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.
    13. 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)

    Citations

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


    Cited by:

    1. Christian Kleiber, 2008. "A Guide to the Dagum Distributions," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 6, pages 97-117, Springer.
    2. Vladimir Hlasny, 2019. "Redistributive Impacts of Fiscal Policies in Mexico: Corrections for Top Income Measurement Problems," LIS Working papers 765, LIS Cross-National Data Center in Luxembourg.
    3. Alexander Sohn & Nadja Klein & Thomas Kneib, 2014. "A New Semiparametric Approach to Analysing Conditional Income Distributions," SOEPpapers on Multidisciplinary Panel Data Research 676, DIW Berlin, The German Socio-Economic Panel (SOEP).
    4. 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.
    5. Sohn, Alexander & Klein, Nadja & Kneib, Thomas, 2014. "A new semiparamtetric approach to analysing Conditional Income Distributions," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100630, Verein für Socialpolitik / German Economic Association.
    6. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and Inequality Measurement: A Comparative Analysis of Correction Methods Using the EU SILC Data," Econometrics, MDPI, vol. 6(2), pages 1-21, June.
    7. Masato Okamoto, 2013. "Extension of the κ-generalized distribution: new four-parameter models for the size distribution of income and consumption," LIS Working papers 600, LIS Cross-National Data Center in Luxembourg.
    8. 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.

    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. 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.
    2. 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.
    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. Markus P. A. Schneider, 2013. "Race & Gender Differences in the Experience of Earnings Inequality in the US from 1995 to 2010," Working Papers 1303, New School for Social Research, Department of Economics.
    5. Markus Schneider, 2013. "Illustrating the Implications of How Inequality is Measured: Decomposing Earnings Inequality by Race and Gender," Journal of Labor Research, Springer, vol. 34(4), pages 476-514, December.
    6. Lidia Ceriani & Paolo Verme, 2022. "Population Changes and the Measurement of Inequality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(2), pages 549-575, July.
    7. Louis Chauvel, 2014. "The Intensity and Shape of Inequality: The ABG Method of Distributional Analysis," LIS Working papers 609, LIS Cross-National Data Center in Luxembourg.
    8. Louis Chauvel, 2016. "The Intensity and Shape of Inequality: The ABG Method of Distributional Analysis," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(1), pages 52-68, March.
    9. 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.
    10. Monique Graf & Desislava Nedyalkova, 2014. "Modeling of Income and Indicators of Poverty and Social Exclusion Using the Generalized Beta Distribution of the Second Kind," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 821-842, December.
    11. 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.
    12. Casilda Lasso de la Vega & Ana Urrutia & Oscar Volij, 2011. "An Axiomatic Characterization Of The Theil Inequality Order," Working Papers 1103, Ben-Gurion University of the Negev, Department of Economics.
    13. Tugce, Cuhadaroglu, 2013. "My Group Beats Your Group: Evaluating Non-Income Inequalities," SIRE Discussion Papers 2013-49, Scottish Institute for Research in Economics (SIRE).
    14. Teixidó Figueras, Jordi & Duro Moreno, Juan Antonio, 2012. "Ecological Footprint Inequality: A methodological review and some results," Working Papers 2072/203168, Universitat Rovira i Virgili, Department of Economics.
    15. 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.
    16. Vladimir Hlasny & Paolo Verme, 2018. "Top Incomes and Inequality Measurement: A Comparative Analysis of Correction Methods Using the EU SILC Data," Econometrics, MDPI, vol. 6(2), pages 1-21, June.
    17. repec:wsr:wpaper:y:2010:i:062 is not listed on IDEAS
    18. Kleiber, Christian, 1997. "The existence of population inequality measures," Economics Letters, Elsevier, vol. 57(1), pages 39-44, November.
    19. Eva Camacho-Cuena & Tibor Neugebauer & Christian Seidl, 2007. "Leaky Buckets Versus Compensating Justice: An Experimental Investigation," Working Papers 74, ECINEQ, Society for the Study of Economic Inequality.
    20. Satya Chakravarty, 2001. "The Variance as a subgroup decomposable measure of inequality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 53(1), pages 79-95, January.
    21. Frank A. Cowell & Emmanuel Flachaire, 2014. "Statistical Methods for Distributional Analysis," Working Papers halshs-01115996, HAL.

    More about this item

    Keywords

    Singh-Maddala distribution; GB2 distribution; inequality; generalized entropy indices; Dagum distribution; generalized Beta of the second kind distribution;
    All these keywords.

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - 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:iza:izadps:dp2831. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.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.