%0 Journal Article
%T Distance-based measures of spatial concentration: introducing a relative density function
%A Lang, G.
%A Marcon, E.
%A Puech, F.
%J Annals of Regional Science
%D 2020
%V 64
%N 2
%I Springer
%@ 05701864 (Issn)
%F Lang_etal2020
%O exported from refbase (http://php.ecofog.gf/refbase/show.php?record=976), last updated on Mon, 08 Feb 2021 11:13:52 -0300
%X 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. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
%K Agglomeration
%K Aggregation
%K Economic geography
%K Point patterns
%K Spatial concentration
%K accuracy assessment
%K econometrics
%K economic activity
%K industrial agglomeration
%K industrial location
%K location decision
%K spatial analysis
%K spatial distribution
%U http://dx.doi.org/10.1007/s00168-019-00946-7
%P 243-265