IDEAS home Printed from https://ideas.repec.org/h/spr/esichp/978-0-387-72796-7_13.html
   My bibliography  Save this book chapter

Modelling Lorenz Curves: Robust and Semi-parametric Issues

In: Modeling Income Distributions and Lorenz Curves

Author

Listed:
  • Frank A. Cowell

    (London School of Economics and Political Science)

  • Maria-Pia Victoria-Feser

    (University of Geneva)

Abstract

Modelling Lorenz curves (LC) for stochastic dominance comparisons is central to the analysis of income distributions. It is conventional to use non-parametric statistics based on empirical income cumulants which are used in the construction of LC and other related second-order dominance criteria. However, although attractive because of its simplicity and its apparent flexibility, this approach suffers from important drawbacks. While no assumptions need to be made regarding the data-generating process (income distribution model), the empirical LC can be very sensitive to data particularities, especially in the upper tail of the distribution. This robustness problem can lead in practice to “wrong” interpretation of dominance orders. A possible remedy for this problem is the use of parametric or semi-parametric models for the data-generating process and robust estimators to obtain parameter estimates. In this paper, we focus on the robust estimation of semi-parametric LC and investigate issues such as sensitivity of LC estimators to data contamination (Cowell and Victoria-Feser, 2002), trimmed LC (Cowell and Victoria-Feser, 2006), and inference for trimmed LC (Cowell and Victoria-Feser, 2003), robust semi-parametric estimation for LC (Cowell and Victoria-Feser, 2007), selection of optimal thresholds for (robust) semi-parametric modelling (Dupuis and Victoria-Feser, 2006), and use both simulations and real data to illustrate these points.

Suggested Citation

  • Frank A. Cowell & Maria-Pia Victoria-Feser, 2008. "Modelling Lorenz Curves: Robust and Semi-parametric Issues," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 13, pages 241-253, Springer.
    • Handle: RePEc:spr:esichp:978-0-387-72796-7_13
    DOI: 10.1007/978-0-387-72796-7_13
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    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. Chiaki Moriguchi & Emmanuel Saez, 2006. "The Evolution of Income Concentration in Japan, 1886-2002: Evidence from Income Tax Statistics," NBER Working Papers 12558, National Bureau of Economic Research, Inc.
    3. Frank A. Cowell & Maria-Pia Victoria-Feser, 2002. "Welfare Rankings in the Presence of Contaminated Data," Econometrica, Econometric Society, vol. 70(3), pages 1221-1233, May.
    4. A. B. Atkinson, 2004. "Income Tax and Top Incomes over the Twentieth Century," Hacienda Pública Española / Review of Public Economics, IEF, vol. 168(1), pages 123-141, march.
    5. 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.
    6. Kopczuk, Wojciech & Saez, Emmanuel, 2004. "Top Wealth Shares in the United States, 1916-2000: Evidence From Estate Tax Returns," National Tax Journal, National Tax Association;National Tax Journal, vol. 57(2), pages 445-487, June.
    7. Frank Cowell & Maria-Pia Victoria-Feser, 2007. "Robust stochastic dominance: A semi-parametric approach," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(1), pages 21-37, April.
    8. Emmanuel Saez & Michael R. Veall, 2005. "The Evolution of High Incomes in Northern America: Lessons from Canadian Evidence," American Economic Review, American Economic Association, vol. 95(3), pages 831-849, June.
    9. Cowell, Frank A. & Victoria-Feser, Maria-Pia, 2006. "Distributional Dominance With Trimmed Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 291-300, July.
    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. Eckerstorfer, Paul & Steiner, Viktor & Wakolbinger, Florian, 2013. "Steuerreformvorschläge in der Diskussion: Eine Mikrosimulationsanalyse der Aufkommens-, Beschäftigungs- und Verteilungswirkungen für Österreich," Discussion Papers 2013/17, Free University Berlin, School of Business & Economics.
    2. Frank A. Cowell & Philippe Kerm, 2015. "Wealth Inequality: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(4), pages 671-710, September.

    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. Frank A. Cowell & Emmanuel Flachaire, 2014. "Statistical Methods for Distributional Analysis," Working Papers halshs-01115996, HAL.
    2. Frank Cowell & Maria-Pia Victoria-Feser, 2007. "Robust stochastic dominance: A semi-parametric approach," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(1), pages 21-37, April.
    3. Anthony B. Atkinson & Thomas Piketty & Emmanuel Saez, 2011. "Top Incomes in the Long Run of History," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 3-71, March.
    4. Stéphane Guerrier & Samuel Orso & Maria-Pia Victoria-Feser, 2018. "Parametric Inference for Index Functionals," Econometrics, MDPI, vol. 6(2), pages 1-11, April.
    5. Gholamreza Hajargasht & William E. Griffiths, 2016. "Inference for Lorenz Curves," Department of Economics - Working Papers Series 2022, The University of Melbourne.
    6. Beat Hulliger & Tobias Schoch, 2014. "Robust, distribution-free inference for income share ratios under complex sampling," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(1), pages 63-85, January.
    7. Frank A. Cowell & Philippe Kerm, 2015. "Wealth Inequality: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(4), pages 671-710, September.
    8. 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.
    9. Cabral, René & García-Díaz, Rocío & Mollick, André Varella, 2016. "Does globalization affect top income inequality?," Journal of Policy Modeling, Elsevier, vol. 38(5), pages 916-940.
    10. Frank Cowell & Emmanuel Flachaire, 2021. "Inequality Measurement: Methods and Data," Post-Print hal-03589066, HAL.
    11. 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.
    12. James B. Davies & Livio Di Matteo, 2021. "Long Run Canadian Wealth Inequality in International Context," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(1), pages 134-164, March.
    13. Facundo Alvaredo, 2007. "The Rich in Argentina over the twentieth century: From the Conservative Republic to the Peronist experience and beyond 1932-2004," Working Papers halshs-00588318, HAL.
    14. Melanie Krause, 2014. "Parametric Lorenz Curves and the Modality of the Income Density Function," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 905-929, December.
    15. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman & Hussain, Saiful Izzuan, 2021. "Measuring income inequality: A robust semi-parametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    16. 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.
    17. Claudia Sanhueza & Ricardo Mayer, 2011. "Top Incomes in Chile using 50 years of household surveys : 1957-2007," Estudios de Economia, University of Chile, Department of Economics, vol. 38(1 Year 20), pages 169-193, June.
    18. Andreas Peichl & Nico Pestel, 2013. "Multidimensional affluence: theory and applications to Germany and the US," Applied Economics, Taylor & Francis Journals, vol. 45(32), pages 4591-4601, November.
    19. Haiyuan Wan & Yangcheng Yu, 2023. "Correction of China's income inequality for missing top incomes," Review of Development Economics, Wiley Blackwell, vol. 27(3), pages 1769-1791, August.
    20. Duquette, Nicolas J., 2018. "Inequality and philanthropy: High-income giving in the United States 1917–2012," Explorations in Economic History, Elsevier, vol. 70(C), pages 25-41.

    More about this item

    Keywords

    Income Distribution; Maximum Likelihood Estimator; Stochastic Dominance; Lorenz Curve; Robust Estimator;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics

    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:spr:esichp:978-0-387-72796-7_13. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.