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Estimation of the Gini coefficient based on two quantiles

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  • Pingsheng Dai
  • Sitong Shen

Abstract

Based on the Palma proposition and the Lorenz fitting curve, this paper estimates the sample Gini coefficient using the income share of the top 10% and bottom 40% of the population. Empirical research shows that the absolute error between the estimated value and sample Gini coefficient is within a hundredth. Monte Carlo simulation shows that the new method has good performance and robustness for estimating Gini coefficients with different sample sizes and different inequality levels. Using the two quantiles in the deciles to estimate the sample Gini coefficient and the Lorenz fitting curve is a practical method.

Suggested Citation

  • Pingsheng Dai & Sitong Shen, 2025. "Estimation of the Gini coefficient based on two quantiles," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-13, February.
  • Handle: RePEc:plo:pone00:0318833
    DOI: 10.1371/journal.pone.0318833
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    References listed on IDEAS

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    1. Chotikapanich, Duangkamon & Griffiths, William E. & Rao, D. S. Prasada, 2007. "Estimating and Combining National Income Distributions Using Limited Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 97-109, January.
    2. Sarabia, J. -M. & Castillo, Enrique & Slottje, Daniel J., 1999. "An ordered family of Lorenz curves," Journal of Econometrics, Elsevier, vol. 91(1), pages 43-60, July.
    3. James B. McDonald, 2008. "Some Generalized Functions for the Size Distribution of Income," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 3, pages 37-55, Springer.
    4. Satya Paul & Sriram Shankar, 2020. "An alternative single parameter functional form for Lorenz curve," Empirical Economics, Springer, vol. 59(3), pages 1393-1402, September.
    5. Chotikapanich, Duangkamon & Valenzuela, Rebecca & Rao, D S Prasada, 1997. "Global and Regional Inequality in the Distribution of Income: Estimation with Limited and Incomplete Data," Empirical Economics, Springer, vol. 22(4), pages 533-546.
    6. Kakwani, N C & Podder, N, 1973. "On the Estimation of Lorenz Curves from Grouped Observations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 278-292, June.
    7. repec:bla:revinw:v:37:y:1991:i:4:p:447-52 is not listed on IDEAS
    8. P. Ortega & G. Martín & A. Fernández & M. Ladoux & A. García, 1991. "A New Functional Form For Estimating Lorenz Curves," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 37(4), pages 447-452, December.
    9. Basmann, R. L. & Hayes, K. J. & Slottje, D. J. & Johnson, J. D., 1990. "A general functional form for approximating the Lorenz curve," Journal of Econometrics, Elsevier, vol. 43(1-2), pages 77-90.
    10. Chotikapanich, Duangkamon, 1993. "A comparison of alternative functional forms for the Lorenz curve," Economics Letters, Elsevier, vol. 41(2), pages 129-138.
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