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Bayesian estimation of Lorenz curve, Gini-index and variance of logarithms in a Pareto distribution

Author

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  • E.I. ABDUL-SATHAR

    (Indian Institute of Management Kozhikode- Calicut - India)

  • E.S. JEEVANAND
  • K.R. MURALEEDHARAN NAIR

Abstract

In this article, we estimate Lorenz curve, Gini-index and variance of logarithms for Pareto distribution using Bayesian framework with a conjugate prior. Our proposed Bayesian estimators are compared using a Monte Carlo study, to the MLE estimator proposed by Moothathu (1990) in terms of variance. It is found that the proposed estimators are highly efficient.

Suggested Citation

  • E.I. Abdul-Sathar & E.S. Jeevanand & K.R. Muraleedharan Nair, 2005. "Bayesian estimation of Lorenz curve, Gini-index and variance of logarithms in a Pareto distribution," Statistica, Department of Statistics, University of Bologna, vol. 65(2), pages 193-205.
    • Handle: RePEc:bot:rivsta:v:65:y:2005:i:2:p:193-205
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    Cited by:

    1. Wang, Dongliang & Zhao, Yichuan & Gilmore, Dirk W., 2016. "Jackknife empirical likelihood confidence interval for the Gini index," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 289-295.

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