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

Gabriel Lang (), Eric Marcon () and Florence Puech ()
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Gabriel Lang: Université Paris-Saclay
Eric Marcon: Université des Antilles, Université de Guyane
Florence Puech: Univ. Paris-Sud, Université Paris-Saclay and CREST

The Annals of Regional Science, 2020, vol. 64, issue 2, No 2, 243-265

Abstract: Abstract For more than a decade, distance-based methods have been widely employed and constantly improved in spatial economics. These methods are a very useful tool for accurately evaluating the spatial distribution of economic activity. We introduce a new distance-based statistical measure for evaluating the spatial concentration of industries. The m function is the first relative density function to be proposed in economics. This tool supplements the typology of distance-based methods recently drawn up by Marcon and Puech (J Econ Geogr 3(4):409–428, 2003). By considering several simulated and real examples, we show the advantages and the limits of the m function for detecting spatial structures in economics.

Keywords: Spatial concentration; Aggregation; Point patterns; Agglomeration; Economic geography (search for similar items in EconPapers)
JEL-codes: C10 C60 R12 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s00168-019-00946-7

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