<?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>2011-2106</journal-id>
<journal-title><![CDATA[Revista de Economía del Caribe]]></journal-title>
<abbrev-journal-title><![CDATA[rev. econ. Caribe]]></abbrev-journal-title>
<issn>2011-2106</issn>
<publisher>
<publisher-name><![CDATA[Editorial Universidad del Norte]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2011-21062019000100071</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Do the determinants of corruption differ between countries with different levels of corruption? A cross-country quantile regression analysis]]></article-title>
<article-title xml:lang="es"><![CDATA[¿Los determinantes de la corrupción difieren entre países con diferentes niveles de corrupción? Un análisis de regresión cuantil entre países]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[PICÓN]]></surname>
<given-names><![CDATA[CRISTIAN]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[BOEHM]]></surname>
<given-names><![CDATA[FREDERIC]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de la Costa CUC  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Pontificia Universidad Católica del Perú  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Peru</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2019</year>
</pub-date>
<numero>23</numero>
<fpage>71</fpage>
<lpage>83</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S2011-21062019000100071&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S2011-21062019000100071&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S2011-21062019000100071&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This contribution responds to a research question posed by Billger &amp; Goel (2009). Are determinants of corruption in highly corrupt countries different from those found in less corrupt countries? To answer this question, we use a cross-country quantile regression model that includes new expli- cative variables. We address some issues of specification we found in the work of Billger &amp; Goel (2009) and we use the broadest and most recent data set used until now in such type of research (170 countries with data from 2018). We find that the variables size of government and share of protestant population are good predictors of the level of corruption only for specific levels of corruption, while other variables such as level of democracy, economic freedom, and income levels are strongly significant for all levels of corruption. In contrast to most of the studies in this area, we do not find the British colonial heritage to be relevant in explaining the current corruption level of a country.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Esta contribución responde a una pregunta de investigación formulada por Billger &amp; Goel (2009). ¿Existen diferentes determinantes de la corrupción en países altamente corruptos en comparación con países menos corruptos? Para responderla, estimamos un modelo de regresión por cu-antiles entre países que agrega nuevas variables explicativas. Abordamos algunos problemas de especificación que encontramos en el trabajo de Billger y Goel (2009) y utilizamos el conjunto de datos más amplio y reciente utilizado hasta ahora en este tipo de investigación (170 países con datos de 2018). Encontramos que las variables del tamaño del gobierno y la proporción de la población protestante son buenos predictores del nivel de corrupción solo para niveles específicos de corrupción, mientras que otras variables como el nivel de democracia, la libertad económica y los niveles de ingreso son muy importantes para todos los niveles de corrupción. A diferencia de la mayoría de los estudios en esta área, no encontramos que la herencia colonial británica sea relevante para explicar el nivel actual de corrupción de un país.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Corruption]]></kwd>
<kwd lng="en"><![CDATA[quantile regression]]></kwd>
<kwd lng="en"><![CDATA[determinants of corruption]]></kwd>
<kwd lng="es"><![CDATA[Corrupción]]></kwd>
<kwd lng="es"><![CDATA[regresión por cuantiles]]></kwd>
<kwd lng="es"><![CDATA[determinantes de la corrupción]]></kwd>
</kwd-group>
</article-meta>
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