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<identifier>oai:HAL:hal-01094082v1</identifier>
<datestamp>2015-02-17</datestamp>
<setSpec>type:ART</setSpec>
<setSpec>subject:math</setSpec>
<setSpec>collection:AGROPARISTECH</setSpec>
<setSpec>collection:CIRAD</setSpec>
<setSpec>collection:UNIV-AG</setSpec>
<setSpec>collection:CNRS</setSpec>
<setSpec>collection:INRA</setSpec>
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<metadata><dc>
<publisher>HAL CCSD</publisher>
<title lang=en>Measures of the geographic concentration of industries: improving distance-based methods</title>
<creator>Marcon, Eric</creator>
<creator>Puech, F.</creator>
<contributor>Ecologie des forêts de Guyane (ECOFOG) ; CNRS - Institut national de la recherche agronomique (INRA) - Centre de coopération internationale en recherche agronomique pour le développement [CIRAD] - Université des Antilles et de la Guyane (UAG) - AgroParisTech</contributor>
<description>International audience</description>
<source>Journal of Economic Geography</source>
<publisher>Oxford University Press (OUP): Policy F</publisher>
<identifier>hal-01094082</identifier>
<identifier>https://hal-agroparistech.archives-ouvertes.fr/hal-01094082</identifier>
<source>https://hal-agroparistech.archives-ouvertes.fr/hal-01094082</source>
<source>Journal of Economic Geography, Oxford University Press (OUP): Policy F, 2010, 10 (5), pp.745-762. <10.1093/jeg/lbp056></source>
<identifier>DOI : 10.1093/jeg/lbp056</identifier>
<language>en</language>
<subject lang=en>Ripley’s K function</subject>
<subject lang=en>M function</subject>
<subject lang=en>Geographic concentration</subject>
<subject lang=en>Distance-based methods</subject>
<subject lang=en>K-density function</subject>
<subject>[MATH.MATH-NA] Mathematics/Numerical Analysis</subject>
<type>Journal articles</type>
<description lang=en>We discuss a property of distance-based measures that has not been addressed with regard to evaluating the geographic concentration of economic activities. The article focuses on the choice between a probability density function of point-pair distances or a cumulative function. We begin by introducing a new cumulative function, M, for evaluating the relative geographic concentration and the co-location of industries in a non-homogeneous spatial framework. Secondly, some rigorous comparisons are made with the leading probability density function of Duranton and Overman (2005), Kd. The merits of the simultaneous use of Kd and M is proved, underlining the complementary nature of the results they provide.</description>
<date>2010-01</date>
</dc>
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