<?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>2448-718X</journal-id>
<journal-title><![CDATA[El trimestre económico]]></journal-title>
<abbrev-journal-title><![CDATA[El trimestre econ]]></abbrev-journal-title>
<issn>2448-718X</issn>
<publisher>
<publisher-name><![CDATA[Fondo de Cultura Económica]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2448-718X2014000200517</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Exploración de la geografía de la innovación en México por medio del análisis de datos espaciales]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Flores Segovia]]></surname>
<given-names><![CDATA[Miguel Alejandro]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Villarreal González]]></surname>
<given-names><![CDATA[Amado]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Tecnológico de Monterrey  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2014</year>
</pub-date>
<volume>81</volume>
<numero>322</numero>
<fpage>517</fpage>
<lpage>544</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2448-718X2014000200517&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2448-718X2014000200517&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2448-718X2014000200517&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN El objetivo de este artículo es investigar la distribución espacial de las industrias en el sector de la innovación en México. Mediante el análisis exploratorio de datos espaciales (AEDE), se presenta un estudio original en un contexto espacial en que el análisis empírico emplea datos georreferenciados recientemente disponibles, por empresa, así como datos de los Censos Económicos de 2009. Se utilizan estadísticas espaciales globales y locales para identificar, cuantificar y localizar clusters espaciales de empresas y su correspondiente composición del empleo. Con esto se muestra la existencia de &#8220;puntos calientes&#8221;, es decir, zonas en donde se presenta una fuerte dinámica de actividades de innovación. Este análisis identifica las regiones más innovadoras con base en siete clusters espaciales de grandes empresas distribuidos por todo el país, principalmente en zonas urbanas y metropolitanas. El estudio contribuye a una mejor comprensión de las condiciones de los clusters de innovación que imperan en el país y quizás ayude en la formulación de políticas específicas de innovación basadas en el tamaño de las empresas y para sectores específicos, esto con el objetivo de acelerar el proceso de innovación regional. También aporta lineamientos para los encargados de formular políticas ansiosos por promover el desarrollo de las economías locales e identificar en dónde se requiere desarrollar, financiar y elaborar sistemas de innovación regionales.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT The objective of this paper is to explore the spatial distribution of industries in the innovation sector in Mexico. Through the use of Explanatory Spatial Data Analysis (ESDA), we aim to present an original study in a spatial context, in which the empirical analysis considers recently available firmlevel georeferenced data, as well as data from the Economic Census of 2009. We use global and local spatial statistics in order to identify, quantify, and locate spatial clusters of firms and their employment composition. By doing so, we aim to show the existence of &#8220;hot-spot&#8221; areas with strong dynamics of innovation activities. The analysis identifies the most innovative regions based on seven spatial clusters of large-size establishments across the country distributed primarily in urban and metropolitan areas. This study contributes to a better understanding of the prevailing conditions of innovation clusters in the country and may help in the design of specific innovation policies tailored to firm size and for specific sectors aiming to accelerate the regional innovation process. It also provides guidance to policymakers eager to promote the development of local economies and identify where regional innovation systems need to be developed, financed, and designed.]]></p></abstract>
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<kwd lng="es"><![CDATA[análisis exploratorio de datos espaciales]]></kwd>
<kwd lng="es"><![CDATA[clusters espaciales]]></kwd>
<kwd lng="es"><![CDATA[innovación]]></kwd>
<kwd lng="es"><![CDATA[políticas industriales]]></kwd>
<kwd lng="es"><![CDATA[sistemas de innovación regionales y sectoriales]]></kwd>
</kwd-group>
</article-meta>
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