untitled
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<identifier>oai:HAL:halshs-00679993v6</identifier>
<datestamp>2018-01-11</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>A typology of distance-based measures of spatial concentration</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>Réseaux Innovation Territoires et Mondialisation (RITM) ; Université Paris-Sud - Paris 11 (UP11)</contributor>
<identifier>halshs-00679993</identifier>
<identifier>https://halshs.archives-ouvertes.fr/halshs-00679993</identifier>
<identifier>https://halshs.archives-ouvertes.fr/halshs-00679993v6/document</identifier>
<identifier>https://halshs.archives-ouvertes.fr/halshs-00679993/file/MARCON-PUECH-Hal%2000679993v6.pdf</identifier>
<source>https://halshs.archives-ouvertes.fr/halshs-00679993</source>
<source>2012</source>
<language>en</language>
<subject lang=en>Spatial concentration</subject>
<subject lang=en>Aggregation</subject>
<subject lang=en>Point patterns</subject>
<subject lang=en>Agglomeration</subject>
<subject lang=en>Economic geography</subject>
<subject>JEL : C.C6.C60</subject>
<subject>JEL : R.R1.R12</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>Over the last decade, distance-based methods have been introduced and then improved in the field of spatial economics to gauge the geographic concentration of activities. There is a growing literature on this theme including new tools, discussions on their specific properties and various applications. However, there is currently no typology of distance-based methods. This paper fills that gap. The proposed classification helps understand all the properties of distance-based methods and proves that they are variations on the same framework.</description>
<date>2012</date>
</dc>
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