The Asymptotic Distribution of the Generalized Gini Indices of Inequality
AbstractThis paper presents the asymptotic distributions of the S-Gini and E-Gini relative and absolute indices of inequality. The generalized Gini indices are defined in terms of Lorenz ordinates and results on the asymptotic covariance matrix of Lorenz ordinates are used to derive the large sample properties of the indices. The methods are illustrated by examining changes in the distribution of nondurable consumption in Canada over the 1980s. The authors find that inequality was lower in 1972 and 1990 than in 1984. Over the entire data period, relative inequality was either static or increased slightly, while absolute inequality declined.
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Bibliographic InfoArticle provided by Canadian Economics Association in its journal Canadian Journal of Economics.
Volume (Year): 28 (1995)
Issue (Month): 4b (November)
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Postal: Canadian Economics Association Prof. Steven Ambler, Secretary-Treasurer c/o Olivier Lebert, CEA/CJE/CPP Office C.P. 35006, 1221 Fleury Est Montréal, Québec, Canada H2C 3K4
Web page: http://economics.ca/cje/
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- Jean-Yves Duclos, 2000. "Gini Indices and the Redistribution of Income," International Tax and Public Finance, Springer, Springer, vol. 7(2), pages 141-162, March.
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Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium, Ghent University, Faculty of Economics and Business Administration
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- Thomas Demuynck, 2012. "An (almost) unbiased estimator for the S-Gini index," Journal of Economic Inequality, Springer, Springer, vol. 10(1), pages 109-126, March.
- Shahateet, Mohammed & Al-Tayyeb, Saud, 2007. "Regional consumption inequalities in Jordan: Empirical study," MPRA Paper 57400, University Library of Munich, Germany.
- 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, ProbabilitÃ e Statistiche Applicate - University of Rome, Dipartimento di Statistica, ProbabilitÃ e Statistiche Applicate - University of Rome, vol. 0(1), pages 107-124.
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