1Ferdowsi University of Mashhad, Faculty of science, Department of Statistics, Mashhad, Iran. PhD. Email: sh.mirzaei@stu.um.ac.ir
2Ferdowsi University of Mashhad, Faculty of science, Department of Statistics, Mashhad, Iran. PhD. Email: grmohtashami@um.ac.ir
3Ferdowsi University of Mashhad, Faculty of science, Department of Statistics, Mashhad, Iran. PhD. Email: m-amini@um.ac.ir ]]>
In this paper, we consider two well-known methods for analysis of the Gini index, which are U-statistics and linearization for some income distributions. In addition, we evaluate two different methods for some properties of their proposed estimators. Also, we compare two methods with resampling techniques in approximating some properties of the Gini index. A simulation study shows that the linearization method performs well compared to the Gini estimator based on U-statistics. A brief study on real data supports our findings.
Key words: Gini coefficient, Income distribution, Linearization method, Resampling techniques, U-statistics.
En este artículo consideramos dos métodos ampliamente conocidos para en análisis del índice Gini, los cuales son U-statistics y linealización. Adicionalmente, evaluamos los dos métodos diferentes con base en las propiedades de los estimadores propuestos sobre distribuciones de la renta. También comparamos los métodos con técnicas de remuestreo aproximando algunas propiedades del índice Gini. Un estudio de simulación muestra que el método de linealización se comporta "bien" comparado con el método basado en U-statistics. Un corto estudio de datos reales confirma nuestro resultado.
Palabras clave: índice Gini, distribuciones de la renta, método de linealización, técnicas de remuestreo, U-statistics.
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Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX:
@ARTICLE{RCEv40n2a01,
AUTHOR = {Mirzaei, Shahryar and Mohtashami Borzadaran, Gholam Reza and Amini, Mohammad}, ]]>
TITLE = {{A Comparative Study of the Gini Coefficient Estimators Based on the Linearization and U-Statistics Methods}},
JOURNAL = {Revista Colombiana de Estadística},
YEAR = {2017},
volume = {40},
number = {2},
pages = {205-221}
}