<?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>2007-0705</journal-id>
<journal-title><![CDATA[Nova scientia]]></journal-title>
<abbrev-journal-title><![CDATA[Nova scientia]]></abbrev-journal-title>
<issn>2007-0705</issn>
<publisher>
<publisher-name><![CDATA[Universidad de La Salle Bajío A. C., Coordinación de Investigación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-07052018000100539</article-id>
<article-id pub-id-type="doi">10.21640/ns.v10i20.1159</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Efectos de la pobreza y de los factores sociodemográficos en la educación superior: un modelo Probit aplicado a México]]></article-title>
<article-title xml:lang="en"><![CDATA[Effects of poverty and sociodemographic factors on high education: a Probit model applied to Mexico]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Marina Clemente]]></surname>
<given-names><![CDATA[José Antonio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Gerónimo Antonio]]></surname>
<given-names><![CDATA[Víctor Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pérez Abarca]]></surname>
<given-names><![CDATA[Juan Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad del Papaloapan  ]]></institution>
<addr-line><![CDATA[Loma Bonita Oaxaca]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad del Mar  ]]></institution>
<addr-line><![CDATA[Puerto Ángel Oaxaca]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2018</year>
</pub-date>
<volume>10</volume>
<numero>20</numero>
<fpage>539</fpage>
<lpage>568</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-07052018000100539&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-07052018000100539&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-07052018000100539&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La pobreza es una situación que condiciona en forma negativa el acceso a bienes y servicios básicos e impide que las personas eleven su nivel y calidad de vida. Tal es la importancia del tema que organismos internacionales como el Banco Mundial (BM), Programa de Naciones Unidas para el Desarrollo (PNUD) y entidades públicas buscan mecanismos para contrarrestar sus efectos. La evidencia empírica muestra la existencia de fuertes vínculos entre la pobreza y la educación, al respecto se ha señalado la presencia de una relación negativa entre ambas variables, es decir, una persona en condición de pobreza tiene una menor probabilidad de acceder a niveles altos de educación, y sin niveles altos de educación frecuentemente se ve forzada a permanecer en pobreza. Sin embargo, no solo la pobreza conlleva a un acceso desigual a la educación, existen otros factores asociados a este fenómeno que favorecen los bajos niveles educativos en los jóvenes en edad escolar. Por tal razón, el objetivo de esta investigación consistió en estimar mediante un modelo Probit el impacto de la pobreza (alimentaria, de capacidades y de patrimonio) y de los factores sociodemográficos en la asistencia escolar del nivel superior de las personas de 19 a 23 años de edad. Con datos del Módulo de Condiciones Socioeconómicas de la Encuesta Nacional de Ingresos y Gastos de los Hogares (MCS-ENIGH) para los años 2008 y 2014 se construyó una base de datos, integrado por el tabulado &#8220;ingreso, concentrado y población&#8221;. Posteriormente se aplicó la metodología de Líneas de Pobreza para identificar y cuantificar el número de personas en condición de pobreza. Mediante el modelo Probit se estimó el cambio marginal en la asistencia escolar ante cambios en las variables explicativas. Los resultados del modelo Probit indicaron que, de los tres niveles de pobreza, la alimentaria es la que disminuye en mayor magnitud la asistencia escolar al nivel superior. El tamaño del hogar mostró que, el incremento de un individuo en el hogar a partir de su valor medio, decrece la probabilidad de la asistencia escolar y de forma inversa, la edad del jefe del hogar indicó que el incremento de un año adicional a partir de su valor medio aumenta la probabilidad de la asistencia escolar. Del conjunto de factores analizados, la variable rural es la que reduce en mayor medida la probabilidad de la asistencia escolar al nivel superior para el segmento de la población analizado; mientras que el nivel educativo del jefe del hogar es el elemento que incrementa en mayor magnitud la probabilidad de la asistencia escolar, es decir, es el instrumento clave para romper el círculo intergeneracional de la pobreza.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Poverty is an issue that constraints people's access to goods and services and prevents them from improving their life quality and level. It is so important that international organizations such as the World Bank (WB), the United Nations Program for Development (UNPD) and other public organisms look for ways to balance its effects. Empirical evidence shows a strong link between poverty and education, the relation between both variables can be positive or negative, that is, a person in poverty has less possibility of accessing high levels of education and without them it is constrained to live in poverty. However, not only poverty brings an unequal access to education, there are other factors associated to this phenomenon that bring on low levels of education to young&#8217;s in school age. For that reason, the aim of this research is to use the Probit model in order to evaluate the effect of poverty (food and assets) and other sociodemographic factors on school attendance at a high level of young persons aged between 19 and 23. Using data of the Módulo de Condiciones Socioeconómicas de la Encuesta Nacional de Ingresos y Gastos de los Hogares (MCS-ENIGH) years 2008 and 2014 a data base was built which integrates &#8220;income, concentrated and population&#8221;. Later, the methodology of &#8220;Lines of Poverty&#8221; was applied to identify and measure the number of persons in poverty condition. By means of the Probit model, the marginal change in school attendance face to changes in the explanatory variables is evaluated. The results of the model show that, of the three levels of poverty, it is the food poverty the one which decreases the most the school attendance at high. The size of the household showed that, the increase of one individual in the household beyond its mean value, decreases the probability of school attendance, the age of the householder showed that, the increase of one additional year beyond its mean values, and increases the probability of school attendance. Of the analyzed factors, it is the rural variable, the one which reduces the most the probability of school attendance at the high level in the analyzed population, whereas, the level of education of the householder is the one which increases the most the probability of school attendance, i.e. It is the key element to break the intergenerational circle of poverty.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[asistencia escolar]]></kwd>
<kwd lng="es"><![CDATA[pobreza]]></kwd>
<kwd lng="es"><![CDATA[factores sociodemográficos]]></kwd>
<kwd lng="es"><![CDATA[modelo Probit]]></kwd>
<kwd lng="en"><![CDATA[school attendance]]></kwd>
<kwd lng="en"><![CDATA[poverty]]></kwd>
<kwd lng="en"><![CDATA[sociodemographic factors]]></kwd>
<kwd lng="en"><![CDATA[Probit model]]></kwd>
</kwd-group>
</article-meta>
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