IDEAS home Printed from https://ideas.repec.org/a/bpj/ecqcon/v30y2015i2p75-87n2.html
   My bibliography  Save this article

On Inferring Income Inequality Measures Using L-moments

Author

Listed:
  • Sreelakshmi N.

    (Indian Statistical Institute, Chennai, India)

  • Asha G.

    (Department of Statistics, Cochin University of Science and Technology, Cochin-22, India)

  • Muraleedharan Nair K. R.

    (Department of Statistics, Cochin University of Science and Technology, Cochin-22, India)

Abstract

L-moments are expectations of linear combinations of order statistics, their use in reliability analysis has been established. In the present paper we study L-moments in relation to income inequality measures. Models characterized by functional relationships between L-moments and income inequality measures are studied. Finally, we define the ordering based on L-moments and study its implications on other existing orderings.

Suggested Citation

  • Sreelakshmi N. & Asha G. & Muraleedharan Nair K. R., 2015. "On Inferring Income Inequality Measures Using L-moments," Stochastics and Quality Control, De Gruyter, vol. 30(2), pages 75-87, December.
    • Handle: RePEc:bpj:ecqcon:v:30:y:2015:i:2:p:75-87:n:2
    DOI: 10.1515/eqc-2015-0007
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/eqc-2015-0007
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/eqc-2015-0007?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
    ---><---

    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. Pundir, Sudesh & Arora, Sangeeta & Jain, Kanchan, 2005. "Bonferroni Curve and the related statistical inference," Statistics & Probability Letters, Elsevier, vol. 75(2), pages 140-150, November.
    2. Mahesh Chandra & Nozer D. Singpurwalla, 1981. "Relationships Between Some Notions Which are Common to Reliability Theory and Economics," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 113-121, February.
    3. Unnikrishnan Nair, N. & Vineshkumar, B., 2011. "Ageing concepts: An approach based on quantile function," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 2016-2025.
    4. Giovanni Maria Giorgi & Michele Crescenzi, 2005. "A look at the Bonferroni inequality measure in a reliability framework," Econometrics 0507004, University Library of Munich, Germany.
    5. Giovanni Maria Giorgi & Michele Crescenzi, 2001. "A proposal of poverty measures based on the Bonferroni inequality index," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 3-16.
    6. Xiaohu Li & Maochao Xu, 2008. "Reversed hazard rate order of equilibrium distributions and a related aging notion," Statistical Papers, Springer, vol. 49(4), pages 749-767, October.
    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. Walter Piesch, 2005. "A look at the structure of some extended Ginis," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 263-296.
    2. Giovanni M. Giorgi & Alessio Guandalini, 2018. "Decomposing the Bonferroni Inequality Index by Subgroups: Shapley Value and Balance of Inequality," Econometrics, MDPI, vol. 6(2), pages 1-16, April.
    3. Mariateresa Ciommi & Chiara Gigliarano & Giovanni Maria Giorgi, 2019. "Bonferroni And De Vergottini Are Back: New Subgroup Decompositions And Bipolarization Measures," Working Papers 439, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    4. Walter Piesch, 2005. "Bonferroni-Index und De Vergottini-Index. Zum 75. und 65. Geburtstag zweier fast vergessener Ungleichheitsmaße," Diskussionspapiere aus dem Institut für Volkswirtschaftslehre der Universität Hohenheim 259/2005, Department of Economics, University of Hohenheim, Germany.
    5. Elena Bárcena-Martin & Jacques Silber, 2017. "The Bonferroni index and the measurement of distributional change," METRON, Springer;Sapienza Università di Roma, vol. 75(1), pages 1-16, April.
    6. Porro Francesco, 2014. "How We Can Evaluate the Inequality in Flint," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 119-128, December.
    7. N. Nair & P. Sankaran & S. Sunoj, 2013. "Quantile based stop-loss transform and its applications," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 167-182, June.
    8. Pundir, Sudesh & Arora, Sangeeta & Jain, Kanchan, 2005. "Bonferroni Curve and the related statistical inference," Statistics & Probability Letters, Elsevier, vol. 75(2), pages 140-150, November.
    9. Satya R. Chakravarty & Pietro Muliere, 2004. "Welfare indicators: a review and new perspectives. 2. Measurement of poverty," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 247-281.
    10. Rolf Aaberge & Steinar Bjerve & Kjell Doksum, 2005. "Decomposition of rank-dependent measures of inequality by subgroups," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 493-503.
    11. Salehi, E.T. & Badía, F.G. & Asadi, M., 2012. "Preservation properties of a homogeneous Poisson process stopped at an independent random time," Statistics & Probability Letters, Elsevier, vol. 82(3), pages 574-585.
    12. Bijamma Thomas & N.N. Midhu & P.G. Sankaran, 2015. "A software reliability model using mean residual quantile function," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1442-1457, July.
    13. Ziqing Dong & Yves Tillé & Giovanni M. Giorgi & Alessio Guandalini, 2021. "Linearization and variance estimation of the Bonferroni inequality index," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1008-1029, July.
    14. Satya R. Chakravarty & Pietro Muliere, 2003. "Welfare indicators: A review and new perspectives. 1. Measurement of inequality," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 457-497.
    15. Devendra Kumar, 2017. "The Singh–Maddala distribution: properties and estimation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1297-1311, November.
    16. Iddo Eliazar & Giovanni M. Giorgi, 2020. "From Gini to Bonferroni to Tsallis: an inequality-indices trek," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 119-153, August.
    17. Abdus Saboor & Muhammad Nauman Khan & Gauss M. Cordeiro & Marcelino A. R. Pascoa & Juliano Bortolini & Shahid Mubeen, 2019. "Modified beta modified-Weibull distribution," Computational Statistics, Springer, vol. 34(1), pages 173-199, March.
    18. Giovanni Maria Giorgi & Michele Crescenzi, 2005. "A look at the Bonferroni inequality measure in a reliability framework," Econometrics 0507004, University Library of Munich, Germany.
    19. Joseph L. Gastwirth & Richard Luo & Qing Pan, 2024. "A statistical examination of wealth inequality within the Forbes 400 richest families in the United States from 2000 to 2023," METRON, Springer;Sapienza Università di Roma, vol. 82(3), pages 329-344, December.
    20. Ebrahimi, Nader & Maasoumi, Esfandiar & Soofi, Ehsan S., 1999. "Ordering univariate distributions by entropy and variance," Journal of Econometrics, Elsevier, vol. 90(2), pages 317-336, June.

    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:bpj:ecqcon:v:30:y:2015:i:2:p:75-87:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.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.