litzenberger2 {REAT} | R Documentation |
Litzenberger-Sternberg Cluster Index
Description
Calculating the Cluster Index by Litzenberger and Sternberg for a given number of I
industries and J
regions
Usage
litzenberger2(e_ij, industry.id, region.id, a_j, p_j, b_ij,
CI.output = "mat", na.rm = TRUE)
Arguments
e_ij |
a vector with the employment of industry |
industry.id |
a vector containing the IDs of the industries |
region.id |
a vector containing the IDs of the regions |
a_j |
a vector containing the areas of the regions |
p_j |
a vector containing the populations of the regions |
b_ij |
a vector containing the numbers of firms of industry |
CI.output |
Type of output: matrix (default: |
na.rm |
logical argument that indicates whether NA values should be excluded before computing results |
Details
The Litzenberger-Sternberg Cluster Index is not standardized and depends on the number of regarded industries and regions.
Value
A matrix or data frame containing IxJ
values of CI
Author(s)
Thomas Wieland
References
Farhauer, O./Kroell, A. (2014): “Standorttheorien: Regional- und Stadtoekonomik in Theorie und Praxis”. Wiesbaden : Springer.
Hoffmann J./Hirsch, S./Simons, J. (2017): “Identification of spatial agglomerations in the German food processing industry”. In: Papers in Regional Science, 96, 1, p. 139-162.
Litzenberger, T./Sternberg, R. (2006): “Der Clusterindex - eine Methodik zur Identifizierung regionaler Cluster am Beispiel deutscher Industriebranchen”. In: Geographische Zeitschrift, 94, 2, p. 209-224.
See Also
litzenberger
, gini.conc
, gini.spec
, locq
, locq2
, ellison.a
, ellison.a2
, ellison.c
, ellison.c2
Examples
data (G.regions.industries)
lss <- litzenberger2(G.regions.industries$emp_all,
G.regions.industries$ind_code, G.regions.industries$region_code,
G.regions.industries$area_sqkm, G.regions.industries$pop,
G.regions.industries$firms, CI.output = "df")
# output as data frame
lss_sort <- lss[order(lss$CI, decreasing = TRUE),]
# Sort decreasing by size of CI
lss_sort[1:5,]