IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v48y2019i3p559-582.html
   My bibliography  Save this article

Jackknife empirical likelihood-based inferences for Lorenz curve with kernel smoothing

Author

Listed:
  • Shan Luo
  • Gengsheng Qin

Abstract

The Lorenz curve describes the wealth proportion for an income-ordered population. In this paper, we introduce a kernel smoothing estimator for the Lorenz curve and propose a smoothed jackknife empirical likelihood method for constructing confidence intervals of Lorenz ordinates. Extensive simulation studies are conducted to evaluate finite sample performances of the proposed methods. A real dataset of Georgia professor’s income is used to illustrate the proposed methods.

Suggested Citation

  • Shan Luo & Gengsheng Qin, 2019. "Jackknife empirical likelihood-based inferences for Lorenz curve with kernel smoothing," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(3), pages 559-582, February.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:3:p:559-582
    DOI: 10.1080/03610926.2017.1417426
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2017.1417426
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2017.1417426?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.

    Citations

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


    Cited by:

    1. Yang Wei & Zhouping Li & Yunqiu Dai, 2022. "Unified smoothed jackknife empirical likelihood tests for comparing income inequality indices," Statistical Papers, Springer, vol. 63(5), pages 1415-1475, October.
    2. Suthakaran Ratnasingam & Spencer Wallace & Imran Amani & Jade Romero, 2024. "Nonparametric confidence intervals for generalized Lorenz curve using modified empirical likelihood," Computational Statistics, Springer, vol. 39(6), pages 3073-3090, September.
    3. Chen, Ruxin & Tabri, Rami V., 2021. "Jackknife empirical likelihood for inequality constraints on regular functionals," Journal of Econometrics, Elsevier, vol. 221(1), pages 68-77.

    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:taf:lstaxx:v:48:y:2019:i:3:p:559-582. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.