IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-00176029.html
   My bibliography  Save this paper

Income distribution and inequality measurement: The problem of extreme values

Author

Listed:
  • Frank A. Cowell

    (STICERD - LSE - London School of Economics and Political Science)

  • Emmanuel Flachaire

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

We examine the statistical performance of inequality indices in the presence of extreme values in the data and show that these indices are very sensitive to the properties of the income distribution. Estimation and inference can be dramatically affected, especially when the tail of the income distribution is heavy, even when standard bootstrap methods are employed. However, use of appropriate semiparametric methods for modelling the upper tail can greatly improve the performance of even those inequality indices that are normally considered particularly sensitive to extreme values.

Suggested Citation

  • Frank A. Cowell & Emmanuel Flachaire, 2007. "Income distribution and inequality measurement: The problem of extreme values," Post-Print halshs-00176029, HAL.
    • Handle: RePEc:hal:journl:halshs-00176029
    DOI: 10.1016/j.jeconom.2007.01.001
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00176029
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-00176029/document
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jeconom.2007.01.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Braulke, Michael, 1983. "An approximation to the Gini coefficient for a population based on sparse information for sub-groups," Journal of Development Economics, Elsevier, vol. 12(1-2), pages 75-81.
    2. Andrew Chesher & Christian Schluter, 2002. "Welfare Measurement and Measurement Error," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(2), pages 357-378.
    3. 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.
    4. Cowell, Frank A & Victoria-Feser, Maria-Pia, 1996. "Robustness Properties of Inequality Measures," Econometrica, Econometric Society, vol. 64(1), pages 77-101, January.
    5. Davidson, Russell & Flachaire, Emmanuel, 2007. "Asymptotic and bootstrap inference for inequality and poverty measures," Journal of Econometrics, Elsevier, vol. 141(1), pages 141-166, November.
    6. Anthony F. Shorrocks & James E. Foster, 1987. "Transfer Sensitive Inequality Measures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 54(3), pages 485-497.
    7. Frank A Cowell & Maria-Pia Victoria-Feser, 2001. "Robust Lorenz Curves: A Semiparametric Approach," STICERD - Distributional Analysis Research Programme Papers 50, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    8. Hall, Peter & Yao, Qiwei, 2003. "Inference in ARCH and GARCH models with heavy-tailed errors," LSE Research Online Documents on Economics 5875, London School of Economics and Political Science, LSE Library.
    9. Singh, S K & Maddala, G S, 1976. "A Function for Size Distribution of Incomes," Econometrica, Econometric Society, vol. 44(5), pages 963-970, September.
    10. Schluter, Christian & Trede, Mark, 2002. "Tails of Lorenz curves," Journal of Econometrics, Elsevier, vol. 109(1), pages 151-166, July.
    11. Cowell, Frank A., 1989. "Sampling variance and decomposable inequality measures," Journal of Econometrics, Elsevier, vol. 42(1), pages 27-41, September.
    12. Peter Hall & Qiwei Yao, 2003. "Inference in Arch and Garch Models with Heavy--Tailed Errors," Econometrica, Econometric Society, vol. 71(1), pages 285-317, January.
    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. Schluter, Christian & van Garderen, Kees Jan, 2009. "Edgeworth expansions and normalizing transforms for inequality measures," Journal of Econometrics, Elsevier, vol. 150(1), pages 16-29, May.
    2. 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.
    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. Richard Burkhauser & Shuaizhang Feng & Stephen Jenkins & Jeff Larrimore, 2011. "Estimating trends in US income inequality using the Current Population Survey: the importance of controlling for censoring," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(3), pages 393-415, September.
    5. Stéphane Guerrier & Samuel Orso & Maria-Pia Victoria-Feser, 2018. "Parametric Inference for Index Functionals," Econometrics, MDPI, vol. 6(2), pages 1-11, April.
    6. Frank A. Cowell & Philippe Kerm, 2015. "Wealth Inequality: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(4), pages 671-710, September.
    7. Davidson, Russell & Flachaire, Emmanuel, 2007. "Asymptotic and bootstrap inference for inequality and poverty measures," Journal of Econometrics, Elsevier, vol. 141(1), pages 141-166, November.
    8. Flachaire, Emmanuel & Nunez, Olivier, 2007. "Estimation of the income distribution and detection of subpopulations: An explanatory model," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3368-3380, April.
    9. 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.
    10. Kleiber, Christian, 1997. "The existence of population inequality measures," Economics Letters, Elsevier, vol. 57(1), pages 39-44, November.
    11. Stephen P. Jenkins & Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2009. "Measuring Inequality Using Censored Data: A Multiple Imputation Approach," Discussion Papers of DIW Berlin 866, DIW Berlin, German Institute for Economic Research.
    12. Frank Cowell & Maria-Pia Victoria-Feser, 2003. "Distribution-Free Inference for Welfare Indices under Complete and Incomplete Information," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 1(3), pages 191-219, December.
    13. Lubrano, Michel & Ndoye, Abdoul Aziz Junior, 2016. "Income inequality decomposition using a finite mixture of log-normal distributions: A Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 830-846.
    14. Stephen P. Jenkins & Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2011. "Measuring inequality using censored data: a multiple‐imputation approach to estimation and inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(1), pages 63-81, January.
    15. Frank A. Cowell & Emmanuel Flachaire, 2014. "Statistical Methods for Distributional Analysis," Working Papers halshs-01115996, HAL.
    16. Zheng, Buhong & J. Cushing, Brian, 2001. "Statistical inference for testing inequality indices with dependent samples," Journal of Econometrics, Elsevier, vol. 101(2), pages 315-335, April.
    17. Christian Schluter, 2018. "Top Incomes, Heavy Tails, and Rank-Size Regressions," Econometrics, MDPI, vol. 6(1), pages 1-16, March.
    18. Camponovo, Lorenzo & Scaillet, Olivier & Trojani, Fabio, 2012. "Robust subsampling," Journal of Econometrics, Elsevier, vol. 167(1), pages 197-210.
    19. Jean-Marie Dufour & Emmanuel Flachaire & Lynda Khalaf, 2019. "Permutation Tests for Comparing Inequality Measures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 457-470, July.
    20. Stephen P. Jenkins & Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2009. "Measuring Inequality Using Censored Data: A Multiple Imputation Approach," Discussion Papers of DIW Berlin 866, DIW Berlin, German Institute for Economic Research.

    More about this item

    Keywords

    inequality measures; statistical performance; robustness;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

    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:hal:journl:halshs-00176029. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.