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REAT (version 3.0.2)

litzenberger: Litzenberger-Sternberg Cluster Index

Description

Calculating the Cluster Index by Litzenberger and Sternberg

Usage

litzenberger(e_ij, e_i, a_j, a, p_j, p, b_ij, b_i)

Arguments

e_ij

a single numeric value with the employment of industry \(i\) in region \(j\)

e_i

a single numeric value with the over-all employment in industry \(i\)

a_j

a single numeric value of the area of region j

a

a single numeric value of the total area

p_j

a single numeric value of the population of region j

p

a single numeric value of the total population

b_ij

a single numeric value of the number of firms of industry \(i\) in region \(j\)

b_i

a single numeric value of the total number of firms of industry \(i\)

Value

A single numeric value of (\(CI\)).

Details

The Litzenberger-Sternberg Cluster Index is not standardized and depends on the number of regarded industries and regions.

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

litzenberger2, gini.conc, gini.spec, locq, locq2, ellison.a, ellison.a2, ellison.c, ellison.c2

Examples

Run this code
# NOT RUN {
# Example from Farhauer/Kroell (2014):
litzenberger(e_ij = 1743, e_i = 5740, a_j = 50, 
a = 576, p_j = 488, p = 4621, b_ij = 35, b_i = 53)
# 21.87491
# }

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