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Unified smoothed jackknife empirical likelihood tests for comparing income inequality indices

Author

Listed:
  • Yang Wei

    (Lanzhou University)

  • Zhouping Li

    (Lanzhou University)

  • Yunqiu Dai

    (Lanzhou University)

Abstract

In the economic and social development, income inequality is an important issue. To measure the income inequality or poverty, many economic indices were introduced in the literature, including the Gini index, Bonferroni index and De Vergottini index, etc. Inference approaches to these indices have been studied extensively in the past decades. By noting that these indices can be written in a unified integral form of the weighted Lorenz curve, this paper develops a smoothed jackknife empirical likelihood (EL) method to make inferences on the difference between indices in a unified framework. Under some mild conditions, we derive the asymptotic distribution of the log EL ratio statistic. Moreover, we carry out extensive Monte Carlo simulation studies and real data analysis to illustrate the performance of the proposed approach.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:stpapr:v:63:y:2022:i:5:d:10.1007_s00362-021-01281-w
    DOI: 10.1007/s00362-021-01281-w
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    References listed on IDEAS

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