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Bias in Gini coefficient estimation for gamma mixture populations

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  • Roberto Vila

    (University of Brasilia)

  • Helton Saulo

    (University of Brasilia
    Federal University of Pelotas)

Abstract

This paper examines the properties of the Gini coefficient estimator for gamma mixture populations and reveals the presence of bias. In contrast, we show that sampling from a gamma distribution yields an unbiased estimator, consistent with prior research (Baydil et al. 2025). We derive an explicit bias expression for the Gini coefficient in gamma mixture populations, which serves as the foundation for proposing bias-corrected Gini estimators. We conduct a Monte Carlo simulation study to evaluate the behavior of the bias-corrected Gini estimators.

Suggested Citation

  • Roberto Vila & Helton Saulo, 2025. "Bias in Gini coefficient estimation for gamma mixture populations," Statistical Papers, Springer, vol. 66(7), pages 1-18, December.
    • Handle: RePEc:spr:stpapr:v:66:y:2025:i:7:d:10.1007_s00362-025-01768-w
    DOI: 10.1007/s00362-025-01768-w
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