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Confidence Interval Estimation for Inequality Indices of the Gini Family

Author

Listed:
  • Paola Palmitesta
  • Corrado Provasi
  • Cosimo Spera

Abstract

In this paper we present some nonparametric bootstrap methods to construct distribution-free confidence intervals for inequality indices belonging to the Gini family. These methods have a coverage accuracy better than that obtained with the asymptotic distribution of their natural estimators, typically the standard normal. The coverage performances of these methods are evaluated for the index R by Gini with a Monte Carlo experiment on samples simulated from the Dagum income model (Type I), which is usually used to describe the income distribution.

Suggested Citation

  • Paola Palmitesta & Corrado Provasi & Cosimo Spera, 2000. "Confidence Interval Estimation for Inequality Indices of the Gini Family," Computational Economics, Springer;Society for Computational Economics, vol. 16(1/2), pages 137-147, October.
    • Handle: RePEc:kap:compec:v:16:y:2000:i:1/2:p:137-147
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    Citations

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    Cited by:

    1. Christian Kleiber, 2008. "A Guide to the Dagum Distributions," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 6, pages 97-117, Springer.
    2. Bhargab Chattopadhyay & Shyamal Krishna De, 2016. "Estimation of Gini Index within Pre-Specified Error Bound," Econometrics, MDPI, vol. 4(3), pages 1-12, June.
    3. Giovanni Maria Giorgi & Paola Palmitesta & Corrado Provasi, 2006. "Asymptotic and bootstrap inference for the generalized Gini indices," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 107-124.
    4. Agostino Tarsitano, 2004. "A new class of inequality measures based on a ratio of L-statistics," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 137-160.

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