krugman.conc2: Krugman coefficient of spatial industry concentration for...
In REAT: Regional Economic Analysis Toolbox
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Examples
Description
Calculating the Krugman coefficient for the spatial concentration of an industry based on regional industry data (normally employment data) compared with a vector of other industries
Usage
1
krugman.conc2(e_ij, e_uj)
Arguments
e_ij
a numeric vector with the employment of the industry i in regions j
e_uj
a data frame with the employment of the industry u in j regions
Details
The Krugman coefficient of industry concentration (K_{i}) is a measure for the dissimilarity of the spatial structure of one industry (i) compared to several others (u) regarding the employment in the j regions. The coefficient K_{iu} varies between 0 (no concentration/same structure) and 2 (maximum difference, that means a complete other spatial structure of the industry compared to the others). The calculation is based on the formulae in Farhauer/Kroell (2013).
Value
A single numeric value (0 < K_{i} < 2)
Author(s)
Thomas Wieland
References
Farhauer, O./Kroell, A. (2013): “Standorttheorien: Regional- und Stadtoekonomik in Theorie und Praxis”. Wiesbaden : Springer.
Nakamura, R./Morrison Paul, C. J. (2009): “Measuring agglomeration”. In: Capello, R./Nijkamp, P. (eds.): Handbook of Regional Growth and Development Theories. Cheltenham: Elgar. p. 305-328.
See Also
gini.conc, gini.spec, krugman.conc, krugman.spec, krugman.spec2, locq
Examples
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# Example from Farhauer/Kroell (2013):
Chemie <- c(20000,11000,31000,8000,20000)
Sozialwesen <- c(40000,10000,25000,9000,16000)
Elektronik <- c(10000,11000,14000,14000,13000)
Holz <- c(7000,7500,11000,1500,36000)
Bergbau <- c(4320, 7811, 3900, 2300, 47560)
# five industries
industries <- data.frame(Chemie, Sozialwesen, Elektronik, Holz)
# data frame with all comparison industries
krugman.conc2(Bergbau, industries)
# returns the Krugman coefficient for the concentration
# of the mining industry (Bergbau) compared to
# chemistry (Chemie), social services (Sozialwesen),
# electronics (Elektronik) and wood industry (Holz)
# 0.8619
Example output
[1] 0.8619321
REAT documentation built on Sept. 5, 2021, 5:18 p.m.
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Description Usage Arguments Details Value Author(s) References See Also Examples
Description
Calculating the Krugman coefficient for the spatial concentration of an industry based on regional industry data (normally employment data) compared with a vector of other industries
Usage
1 | krugman.conc2(e_ij, e_uj)
|
Arguments
e_ij |
a numeric vector with the employment of the industry i in regions j |
e_uj |
a data frame with the employment of the industry u in j regions |
Details
The Krugman coefficient of industry concentration (K_{i}) is a measure for the dissimilarity of the spatial structure of one industry (i) compared to several others (u) regarding the employment in the j regions. The coefficient K_{iu} varies between 0 (no concentration/same structure) and 2 (maximum difference, that means a complete other spatial structure of the industry compared to the others). The calculation is based on the formulae in Farhauer/Kroell (2013).
Value
A single numeric value (0 < K_{i} < 2)
Author(s)
Thomas Wieland
References
Farhauer, O./Kroell, A. (2013): “Standorttheorien: Regional- und Stadtoekonomik in Theorie und Praxis”. Wiesbaden : Springer.
Nakamura, R./Morrison Paul, C. J. (2009): “Measuring agglomeration”. In: Capello, R./Nijkamp, P. (eds.): Handbook of Regional Growth and Development Theories. Cheltenham: Elgar. p. 305-328.
See Also
gini.conc, gini.spec, krugman.conc, krugman.spec, krugman.spec2, locq
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # Example from Farhauer/Kroell (2013):
Chemie <- c(20000,11000,31000,8000,20000)
Sozialwesen <- c(40000,10000,25000,9000,16000)
Elektronik <- c(10000,11000,14000,14000,13000)
Holz <- c(7000,7500,11000,1500,36000)
Bergbau <- c(4320, 7811, 3900, 2300, 47560)
# five industries
industries <- data.frame(Chemie, Sozialwesen, Elektronik, Holz)
# data frame with all comparison industries
krugman.conc2(Bergbau, industries)
# returns the Krugman coefficient for the concentration
# of the mining industry (Bergbau) compared to
# chemistry (Chemie), social services (Sozialwesen),
# electronics (Elektronik) and wood industry (Holz)
# 0.8619
|
Example output
[1] 0.8619321
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