Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, EpiSciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Journal articles

Distance-based measures of spatial concentration: Introducing a relative density function

Abstract : For a decade, distance-based methods have been widely employed and constantly improved in the field of spatial economics. These methods are a very useful tool for accurately evaluating the spatial distribution of plants or retail stores, for example (Duranton and Overman, 2008). In this paper, we introduce a new distance-based statistical measure for evaluating the spatial concentration of economic activities. To our knowledge, the m function is the first relative density function to be proposed in the economics literature. This tool supplements the typology of distance-based methods recently drawn up by Marcon and Puech (2012). By considering several theoretical and empirical examples, we show the advantages and the limits of the m function for detecting spatial structures in economics.
Document type :
Journal articles
Complete list of metadata

Cited literature [68 references]  Display  Hide  Download
Contributor : Florence Puech Connect in order to contact the contributor
Submitted on : Thursday, October 24, 2019 - 10:29:01 PM
Last modification on : Wednesday, November 3, 2021 - 4:04:18 AM
Long-term archiving on: : Saturday, January 25, 2020 - 6:43:52 PM


Files produced by the author(s)



Gabriel Lang, Eric Marcon, Florence Puech. Distance-based measures of spatial concentration: Introducing a relative density function. The Annals of Regional Science, 2020, 64 (2), pp.243-265. ⟨10.1007/s00168-019-00946-7⟩. ⟨hal-01082178v4⟩



Record views


Files downloads