Description Usage Arguments Details Value Author(s) References See Also Examples
Calculating three measures of industry concentration (Gini, Krugman, Hoover) for a set of I industries
1 |
e_ij |
a numeric vector with the employment of the industry i in region j |
industry.id |
a vector containing the IDs of the industries i |
region.id |
a vector containing the IDs of the regions j |
na.rm |
logical argument that indicates whether NA values should be excluded before computing results |
This function is a convenient wrapper for all functions calculating measures of spatial concentration of industries (Gini, Krugman, Hoover)
A matrix
with three columns (Gini coefficient, Krugman coefficient, Hoover coefficient) and I rows (one for each regarded industry).
Thomas Wieland
Farhauer, O./Kroell, A. (2014): “Standorttheorien: Regional- und Stadtoekonomik in Theorie und Praxis”. Wiesbaden : Springer.
Schaetzl, L. (2000): “Wirtschaftsgeographie 2: Empirie”. Paderborn : Schoeningh.
gini.conc
, krugman.conc2
, hoover
1 2 3 4 5 | data(G.regions.industries)
conc_i <- conc (e_ij = G.regions.industries$emp_all,
industry.id = G.regions.industries$ind_code,
region.id = G.regions.industries$region_code)
|
Spatial concentration of industries
I = 17 industries, J = 16 regions
H i G i K i
WZ08-B 0.22959050 0.42334831 0.45675385
WZ08-C 0.09933363 0.17047620 0.26813759
WZ08-D 0.07754576 0.12509360 0.16260016
WZ08-E 0.11972072 0.16742909 0.20369011
WZ08-F 0.07676634 0.15357575 0.16996098
WZ08-G 0.03034962 0.05471323 0.07977056
WZ08-H 0.06006957 0.11921850 0.10076748
WZ08-I 0.05177262 0.09939075 0.11450791
WZ08-J 0.10230712 0.22605802 0.24450967
WZ08-K 0.08982871 0.17610712 0.20565974
WZ08-L 0.09798632 0.16784764 0.17472656
WZ08-M 0.06490185 0.14760918 0.14931991
WZ08-N 0.06714816 0.08575299 0.09053327
WZ08-P 0.03019678 0.05053848 0.07043586
WZ08-Q 0.04679962 0.06170335 0.06406058
WZ08-R 0.09424708 0.16748405 0.17023603
WZ08-S 0.04507988 0.07246697 0.06441360
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