<?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>2007-8064</journal-id>
<journal-title><![CDATA[Entreciencias: diálogos en la sociedad del conocimiento]]></journal-title>
<abbrev-journal-title><![CDATA[Entreciencias: diálogos soc. conoc.]]></abbrev-journal-title>
<issn>2007-8064</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Escuela Nacional de Estudios Superiores]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-80642021000100006</article-id>
<article-id pub-id-type="doi">10.22201/enesl.20078064e.2021.23.77338</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Estimation Of Municipal Income Distribution in Mexico]]></article-title>
<article-title xml:lang="es"><![CDATA[Estimación de la distribución del ingreso municipal en México]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Gallardo Del Ángel]]></surname>
<given-names><![CDATA[Roberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ojeda Ramírez]]></surname>
<given-names><![CDATA[Mario Miguel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cruz López]]></surname>
<given-names><![CDATA[Cecilia]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Veracruzana  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2021</year>
</pub-date>
<volume>9</volume>
<numero>23</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-80642021000100006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-80642021000100006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-80642021000100006&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT  Purpose:  To offer an estimation of income distribution measures for municipalities in Mexico for year 2015, and also an analysis of municipal grants on income inequality.  Methodological design:  We constructed Gini and Atkinson indexes using microdata from the Mexican inter-census survey 2015. We use these inequality indexes along with other several features of poverty and marginality to perform cluster analysis and classify municipalities. From our cluster analysis, we classified the municipalities in four groups: low, medium-low, medium-high and high-income inequality. Afterwards, we performed weighted least squares regressions to observe the effect of fiscal variables on inequality in each group.  Results:  Although the objective of federal grants has been poverty instead of inequality, we offer evidence that income inequality is inversely affected by the design of federal grants. The regression analysis shows that conditional grants designed to reduce poverty might be increasing inequality, while unconditional grants may help to reduce income inequality even though this is not their policy objective.  Research limitations:  The main limitation might be the lack of local statistics for other years to perform a dynamic analysis.  Findings:  The overall effect of conditional grants on income distribution is small but still positive, showing that conditional grants do not reduce income inequality. The estimates show that the total effect is for lower income inequality, especially in those municipalities with high and very high inequality.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN  Objetivo:  ofrecer una estimación de las medidas de distribución del ingreso para los municipios de México para el año 2015, y también un análisis de las subvenciones municipales sobre desigualdad de ingresos.  Diseño metodológico:  se construyeron índices de Gini y Atkinson usando microdatos de la Encuesta Intercensal Mexicana de 2015. Estos índices, junto con otras características de pobreza y marginalidad, se utilizaron para realizar un análisis de conglomerados para clasificar los municipios. Utilizando este análisis se clasificaron los municipios en cuatro grupos: desigualdad de ingresos baja, media-baja, media-alta y alta. Se realizó regresión de mínimos cuadrados ponderados para observar el efecto de las variables fiscales sobre la desigualdad.  Resultados:  aunque el enfoque de las subvenciones federales ha sido la pobreza en lugar de la desigualdad, se ofrece evidencia de que la desigualdad de ingresos se ve afectada inversamente por el diseño de las subvenciones federales. La regresión muestra que las subvenciones condicionales diseñadas para reducir la pobreza pueden estar aumentando la desigualdad, mientras que las subvenciones incondicionales pueden ayudar a reducir la desigualdad de ingresos, aunque este no sea el objetivo de esta política.  Limitaciones de la investigación:  la principal limitación es la falta de datos a nivel local para otros años para poder realizar un análisis dinámico.  Hallazgos:  el efecto general de la distribución de las subvenciones federales sigue siendo positivo. El efecto total es por una menor desigualdad de ingresos, especialmente en aquellos municipios con alta y muy alta desigualdad.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Gini index]]></kwd>
<kwd lng="en"><![CDATA[Atkinson index]]></kwd>
<kwd lng="en"><![CDATA[cluster analysis]]></kwd>
<kwd lng="en"><![CDATA[regressions analysis]]></kwd>
<kwd lng="es"><![CDATA[Índice de Gini]]></kwd>
<kwd lng="es"><![CDATA[Índice de Atkinson]]></kwd>
<kwd lng="es"><![CDATA[análisis de conglomerados]]></kwd>
<kwd lng="es"><![CDATA[análisis de regresión]]></kwd>
</kwd-group>
</article-meta>
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