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An investigation of the performance of parametric functional forms for the Lorenz curve

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  • Thitithep Sitthiyot
  • Kanyarat Holasut

Abstract

Given that an excellent performance of any parametric functional form for the Lorenz curve that is based on a single country case study and a limited range of distribution must be treated with great caution, this study investigates the performance of a single-parameter functional form proposed by Paul and Shankar (2020) who use income data of Australia to show that their functional form is superior to the other existing widely used functional forms considered in their study. By using both mathematical proof and empirical data of 40 countries around the world, this study demonstrates that Paul and Shankar (2020)’s functional form not only fails to fit the actual observations well but also is generally outperformed by the other popular functional forms considered in their study. Moreover, to overcome the limitation of the performance of a single-parameter functional form on the criterion of the estimated Gini index, this study employs a functional form that has more than one parameter in order to show that, by and large, it performs better than all popular single-parameter functional forms considered in Paul and Shankar (2020)’s study. Thus, before applying any functional form to estimate the Lorenz curve, policymakers should check if it could describe the shape of income distributions of different countries through the changes in parameter values and yield the values of the estimated Gini index that are close to their observed data. Using a functional form that does not fit the actual observations could adversely affect inequality measures and income distribution policies.

Suggested Citation

  • Thitithep Sitthiyot & Kanyarat Holasut, 2023. "An investigation of the performance of parametric functional forms for the Lorenz curve," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-21, June.
    • Handle: RePEc:plo:pone00:0287546
    DOI: 10.1371/journal.pone.0287546
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    References listed on IDEAS

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    1. Thitithep Sitthiyot & Kanyarat Holasut, 2021. "A simple method for estimating the Lorenz curve," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-9, December.
    2. 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.
    3. Thitithep Sitthiyot & Kanyarat Holasut, 2021. "A simple method for estimating the Lorenz curve," Papers 2112.15291, arXiv.org.
    4. Kakwani, Nanak C & Podder, N, 1976. "Efficient Estimation of the Lorenz Curve and Associated Inequality Measures from Grouped Observations," Econometrica, Econometric Society, vol. 44(1), pages 137-148, January.
    5. Satya Paul & Sriram Shankar, 2020. "An alternative single parameter functional form for Lorenz curve," Empirical Economics, Springer, vol. 59(3), pages 1393-1402, September.
    6. Kakwani, Nanak, 1980. "On a Class of Poverty Measures," Econometrica, Econometric Society, vol. 48(2), pages 437-446, March.
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