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

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  • 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
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    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. 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.

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