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<identifier>oai:HAL:halshs-00372617v1</identifier>
<datestamp>2018-01-11</datestamp>
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<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, Florence</creator>
<contributor>Ecologie des forêts de Guyane (ECOFOG) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD) - Institut National de la Recherche Agronomique (INRA) - Université des Antilles et de la Guyane (UAG) - AgroParisTech - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Laboratoire d'économie des transports (LET) ; Université Lumière - Lyon 2 (UL2) - École Nationale des Travaux Publics de l'État (ENTPE) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<description>JEL : C40 ; C60 ; R12 ; L60</description>
<identifier>halshs-00372617</identifier>
<identifier>https://halshs.archives-ouvertes.fr/halshs-00372617</identifier>
<identifier>https://halshs.archives-ouvertes.fr/halshs-00372617/document</identifier>
<identifier>https://halshs.archives-ouvertes.fr/halshs-00372617/file/HAL_Marcon_Puech_-_MeasuresOfTheGeographicConcentrationOfIndustriesImprovingDistanceBasedMethods.pdf</identifier>
<source>https://halshs.archives-ouvertes.fr/halshs-00372617</source>
<source>JEL : C40 ; C60 ; R12 ; L60. 2009</source>
<language>en</language>
<subject lang=en>Geographic concentration</subject>
<subject lang=en>Distance-based methods</subject>
<subject lang=en>Ripley's K function</subject>
<subject lang=en>M function</subject>
<subject>[SHS.ECO] Humanities and Social Sciences/Economies and finances</subject>
<type>info:eu-repo/semantics/preprint</type>
<type>Preprints, Working Papers, ...</type>
<description lang=en>This study introduces two new measures of spatial concentration. The proposed M functions constitute an extension to Ripley's functions (Ripley, 1976, 1977). They allow the evaluation of the relative geographic concentration and co-location of industries in a non-homogeneous spatial framework. Some rigorous comparisons with similar recently developed tools prove the relevance of the M functions in the field of spatial economics.</description>
<date>2009-04-01</date>
</dc>
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