New functional forms of Lorenz curves by maximizing Tsallis entropy of income share function under the constraint on generalized Gini index

• Published in: Physica A Vol. 511; pp. 280 - 288
• Main Authors: Khosravi Tanak, A., Mohtashami Borzadaran, G.R., Ahmadi, Jafar
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2018
• Subjects: Generalized Gini index; Lorenz curve; Maximum entropy; Share function; Tsallis entropy; Share function; Lorenz curve; Tsallis entropy; Generalized Gini index; Maximum entropy
• ISSN: 0378-4371; 1873-2119
• DOI: 10.1016/j.physa.2018.07.050

The Lorenz curve is one of the most powerful tools in the analysis of the size distribution of income and wealth. In the past decades, many authors have proposed different functional forms for estimating Lorenz curves using a variety of approaches. In this paper, new functional forms are derived by maximizing Tsallis entropy of income share function subject to a given generalized Gini index. The obtained Lorenz curves are fitted to the income data sets of three Asian countries in 1988 and their relative performances with respect to some well-known parametric models of Lorenz curves are compared using two types of goodness of fit measures. •We approximate the Lorenz curve by maximum Tsallis entropy of income share function.•We fit the obtained model to the decile data of three Asian countries.•We find that the obtained model fit the data better than alternative models.