<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0120-1751</journal-id>
<journal-title><![CDATA[Revista Colombiana de Estadística]]></journal-title>
<abbrev-journal-title><![CDATA[Rev.Colomb.Estad.]]></abbrev-journal-title>
<issn>0120-1751</issn>
<publisher>
<publisher-name><![CDATA[Departamento de Estadística - Universidad Nacional de Colombia.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0120-17512007000200009</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Central Limit Theorems for S-Gini and Theil Inequality Coefficients]]></article-title>
<article-title xml:lang="es"><![CDATA[Teoremas central del límite para el S-Gini y el coeficiente de Theil]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[MARTÍNEZ-CAMBLOR]]></surname>
<given-names><![CDATA[PABLO]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Fundación Caubet-Cimera Illes Balears  ]]></institution>
<addr-line><![CDATA[Mallorca ]]></addr-line>
<country>España</country>
</aff>
<pub-date pub-type="pub">
<day>15</day>
<month>12</month>
<year>2007</year>
</pub-date>
<pub-date pub-type="epub">
<day>15</day>
<month>12</month>
<year>2007</year>
</pub-date>
<volume>30</volume>
<numero>2</numero>
<fpage>287</fpage>
<lpage>300</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0120-17512007000200009&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0120-17512007000200009&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0120-17512007000200009&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[The Hungarian Construction (Komlós et al. 1975) is used for getting a proof of asymptotic normality of S-Gini coefficient; this method is very interesting because it can be used to check asymptotic normality of other income inequality measures as Theil coefficient. Besides, explicit expressions of asymptotic means and variances are given for S-Gini and Theil estimators. Finally, to illustrate the performance of obtained results, we carry out a simulation study comparing the asymptotic and Smoothed Bootstrap approximations.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Se usa el Proceso Húngaro (Komlós et al. 1975) para derivar la normalidad asintótica del S-Gini; Este método es muy interesante ya que puede ser usado para demostrar la normalidad asintótica de otros coeficientes usados para medir la desigualdad de ingresos como el de Theil. Se consiguen expresiones explícitas para la media y la varianza del S-Gini y del coeficiente de Theil. Finalmente, se realiza un estudio de simulación, en el que se compara el rendimiento de la aproximación asintótica propuesta y del método Bootstrap Suavizado.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[S-Gini index]]></kwd>
<kwd lng="en"><![CDATA[Theil index]]></kwd>
<kwd lng="en"><![CDATA[Hungarian construction]]></kwd>
<kwd lng="en"><![CDATA[Kernel density estimation]]></kwd>
<kwd lng="es"><![CDATA[índice S-Gini]]></kwd>
<kwd lng="es"><![CDATA[índice de Theil]]></kwd>
<kwd lng="es"><![CDATA[proceso húngaro]]></kwd>
<kwd lng="es"><![CDATA[estimación kernel para la densidad]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[  <font size="2" face="verdana">      <p> <b> <font size="4">     <center> Central Limit Theorems for S-Gini and Theil Inequality Coefficients </center> </font> </b> </p>      <p> <b> <font size="3">     <center> Teoremas central del l&iacute;mite para el S-Gini y el coeficiente de Theil </center> </font> </b> </p>      <p>     <center> PABLO MART&Iacute;NEZ-CAMBLOR<sup>1</sup> </center> </p>      <p> <sup>1</sup>Fundaci&oacute;n Caubet-Cimera Illes Balears, Mallorca, Espa&ntilde;a. Programa de epidemiolog&iacute;a e investigaci&oacute;n cl&iacute;nica. Email: <a href="mailto:martinez@caubet-cimera.es">martinez@caubet-cimera.es</a>     <br> </p>  <hr size="1">      <p> <b>     ]]></body>
<body><![CDATA[<center> Abstract </center> </b> </p>      <p> The Hungarian Construction (Koml&oacute;s et al. 1975) is used for getting a proof of asymptotic normality of S-Gini coefficient; this method is very interesting because it can be used to check asymptotic normality of other income inequality measures as Theil coefficient. Besides, explicit expressions of asymptotic means and variances are given for S-Gini and Theil estimators. Finally, to illustrate the performance of obtained results, we carry out a simulation study comparing the asymptotic and Smoothed Bootstrap approximations. </p>      <p> <b> Key words: </b> S-Gini index, Theil index, Hungarian construction, Kernel density estimation. </p>  <hr size="1">      <p> <b>     <center> Resumen </center> </b> </p>      <p> Se usa el Proceso H&uacute;ngaro (Koml&oacute;s et al. 1975) para derivar la normalidad asint&oacute;tica del S-Gini; Este m&eacute;todo es muy interesante ya que puede ser usado para demostrar la normalidad asint&oacute;tica de otros coeficientes usados para medir la desigualdad de ingresos como el de Theil. Se consiguen expresiones expl&iacute;citas para la media y la varianza del S-Gini y del coeficiente de Theil. Finalmente, se realiza un estudio de simulaci&oacute;n, en el que se compara el rendimiento de la aproximaci&oacute;n asint&oacute;tica propuesta y del m&eacute;todo Bootstrap Suavizado. </p>      <p> <b> Palabras clave: </b> &iacute;ndice S-Gini, &iacute;ndice de Theil, proceso h&uacute;ngaro, estimaci&oacute;n <em>kernel</em> para la densidad. </p>  <hr size="1">      <p> Texto completo disponible en <a href="pdf/rce/v30n2/v30n2a09.pdf">PDF</a> </p>  <hr size="1">      <p> <b> <font size="3"> References </font> </b> </p>       <!-- ref --><p> 1. Billingsley, P. (1968), <i>Convergence of Probability Measures</i>, John Wiley and Sons, New York, United States. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000022&pid=S0120-1751200700020000900001&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p> 2. 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