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The chi-square statistic as an income inequality index | ||
| AUT Journal of Mathematics and Computing | ||
| مقاله 5، دوره 6، شماره 4، 2025، صفحه 327-340 اصل مقاله (691.49 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajmc.2024.22945.1205 | ||
| نویسندگان | ||
| Shahryar Mirzaei* 1؛ Seyed Mahdi Amir Jahanshahi2 | ||
| 1Department of Statistics, Payame Noor University, Tehran, Iran | ||
| 2Department of Statistics, University of Sistan and Baluchestan, Zahedan, Iran | ||
| چکیده | ||
| This article presents a novel concept known as the chi-square inequality index, developed through the utilization of the chi-square distance function. The study delves into the essential characteristics necessary for an effective inequality index. Additionally, a detailed formulation for the chi-square inequality curve is provided within key inequality models. A comparative analysis between the chi-square curve and the conventional Lorenz curve is conducted. Furthermore, a stochastic order based on the chi-square inequality curve is introduced. The research includes a simulation analysis to explore the statistical properties of the proposed sampling estimator. To conclude, the article highlights the effectiveness of this index through an application to real-world data. | ||
| کلیدواژه‌ها | ||
| Chi-square index؛ Income inequalty index؛ Lorenz curve | ||
| مراجع | ||
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[1] E. B. Andersen, A goodness of fit test for the rasch model, Psychometrika, 38 (1973), pp. 123–140.
[2] A. Arcagni and F. Porro, The Graphical Representation of Inequality, Revista Colombiana de Estad´ıstica, 37 (2014), pp. 419–437.
[3] B. C. Arnold, On zenga and bonferroni curves, METRON, 73 (2015), pp. 25–30.
[4] S.-H. Cha, Comprehensive survey on distance/similarity measures between probability density functions, Int. J. Math. Model. Meth. Appl. Sci., 1 (2007), pp. 300–307.
[5] F. A. Cowell, Measurement of inequality, in Handbook of Income Distribution, vol. 1, Elsevier, 2000, ch. 2, pp. 87–166.
[6] G. M. Giorgi and C. Gigliarano, The Gini concentration index: A review of the inference literature, Journal of Economic Surveys, 31 (2017), pp. 1130–1148.
[7] C. Kleiber and S. Kotz, Statistical Size Distributions in Economics and Actuarial Sciences, Wiley Series in Probability and Statistics, John Wiley & Sons, Inc, 2003.
[8] R. G. Miller, Simultaneous Statistical Inference, Springer New York, NY, 2nd ed., 2012.
[9] S. Mirzaei, G. R. Mohtashami Borzadaran, M. Amini, and H. Jabbari, Some properties of the Canberra inequality index, Hacet. J. Math. Stat., 46 (2017), pp. 1159–1174.
[10] L. Pasquazzi and M. Zenga, Components of Gini, Bonferroni, and Zenga inequality indexes for EU income data, Journal of Official Statistics, 34 (2018), pp. 149–180.
[11] M. Polisicchio and F. Porro, A comparison between Lorenz L(p) curve and Zenga I(p) curve, Statistica Applicata, 21 (2011), pp. 289–301.
[12] J. M. Sarabia, Parametric lorenz curves: Models and applications, in Modeling Income Distributions and Lorenz Curves, vol. 5, Springer New York, 2008, ch. 9, pp. 167–190.
[13] J. M. Sarabia and V. ´ıa, Explicit expressions of the Pietra index for the generalized function for the size distribution of income, Physica A: Statistical Mechanics and its Applications, 416 (2014), pp. 582–595. | ||
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