<?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>0186-7202</journal-id>
<journal-title><![CDATA[Estudios Económicos (México, D.F.)]]></journal-title>
<abbrev-journal-title><![CDATA[Estud. Econ. (México, D.F.)]]></abbrev-journal-title>
<issn>0186-7202</issn>
<publisher>
<publisher-name><![CDATA[El Colegio de México A.C.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0186-72022024000100121</article-id>
<article-id pub-id-type="doi">10.24201/ee.v39i1.449</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[The influence of femicide on criminal behavior: An empirical approach using economic complexity for crime prevention in Mexico]]></article-title>
<article-title xml:lang="es"><![CDATA[La influencia del feminicidio en el comportamiento criminal: un enfoque empírico basado en la complejidad económica para la prevención del delito en México]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lugo-Delgadillo]]></surname>
<given-names><![CDATA[Max]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Entropia AI  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2024</year>
</pub-date>
<volume>39</volume>
<numero>1</numero>
<fpage>121</fpage>
<lpage>157</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0186-72022024000100121&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0186-72022024000100121&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0186-72022024000100121&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Following the economic complexity methodology introduced by Hausmann et al. (2013), this study establishes an order of crime evolution in Mexico. This ordering is based on the complexity of crimes, as determined by the capabilities required to commit them. According to the study, the least complex crimes in Mexico include robbery in collective public transport, robbery in individual transport, counterfeiting, and auto parts theft. On the other hand, the crimes characterized by the highest complexity involve organized crime, intentional and unintentional homicide, and the trafficking of minors. Furthermore, the analysis reveals that femicide and rape exhibit the most significant centrality or influence within the criminal network. According to the model, crimes associated with violence against women are those that most increase the probability of committing another crime. Therefore, targeted prevention efforts aimed at reducing femicide and rape may substantially impact overall levels of criminality in Mexico. This study also highlights the importance of addressing violence against women in designing crime prevention policies in Mexico. Moreover, the methodology adopted in this study can be reinterpreted as a spectral clustering algorithm and thus also contributes to the literature on machine learning applications in public policy design.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: Bajo la metodología de complejidad económica propuesta por Hausmann et al. (2013), esta investigación estableció un ordenamiento de la evolución del crimen en México. Este ordenamiento se basa en la complejidad de los delitos, determinada por las capacidades requeridas para cometerlos. De acuerdo con esta investigación, los delitos con menor complejidad en México incluyen el robo en transporte público colectivo, robo en transporte individual, falsificación y robo de autopartes. Por otro lado, los delitos con mayor complejidad están relacionados con el crimen organizado, el homicidio intencional e involuntario y el tráfico de menores. Además, el análisis reveló que el feminicidio y la violación exhiben la centralidad o influencia más significativa dentro de la red criminal. Según el modelo, los delitos asociados con la violencia contra las mujeres son los que más aumentan la probabilidad de cometer otro delito. Por lo tanto, los esfuerzos de prevención dirigidos a reducir el feminicidio y la violación pueden tener un impacto sustancial en los niveles generales de criminalidad en México. Este estudio también destaca la importancia de abordar la violencia contra las mujeres en el diseño de políticas de prevención del delito en México. Además, la metodología adoptada en este estudio puede ser reinterpretada como un algoritmo de agrupamiento espectral y, por lo tanto, también contribuye a la literatura sobre aplicaciones de aprendizaje automático en el diseño de políticas públicas.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[economic complexity]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
<kwd lng="en"><![CDATA[femicide]]></kwd>
<kwd lng="en"><![CDATA[crime prevention]]></kwd>
<kwd lng="es"><![CDATA[complejidad económica]]></kwd>
<kwd lng="es"><![CDATA[aprendizaje automático]]></kwd>
<kwd lng="es"><![CDATA[feminicidio]]></kwd>
<kwd lng="es"><![CDATA[prevención de la delincuencia]]></kwd>
</kwd-group>
</article-meta>
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