REAT (version 3.0.3)

krugman.spec2: Krugman coefficient of regional specialization for more than two regions

Description

Calculating the Krugman coefficient for the specialization of one region based on regional industry data (normally employment data) compared with a vector of other regions

Usage

krugman.spec2(e_ij, e_il)

Arguments

e_ij

a numeric vector with the employment of the industries \(i\) in region \(j\)

e_il

a data frame with the employment of the industries \(i\) in \(l\) regions

Value

A single numeric value (\(0 < K_{jl} < 2\))

Details

The Krugman coefficient of regional specialization (\(K_{jl}\)) is a measure for the dissimilarity of the industrial structure of regions (\(j\) and other regions, \(l\)) regarding the employment in the \(i\) industries in these regions. The coefficient \(K_{jl}\) varies between 0 (no specialization/same structure) and 2 (maximum difference, that means there is no single industry localized in both regions).

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.spec, krugman.conc, krugman.conc2, locq

Examples

# NOT RUN {
# Example from Farhauer/Kroell (2013):
Sweden <- c(45000, 15000, 32000, 10000, 30000)
Norway <- c(35000, 12000, 30000, 8000, 22000)
Denmark <- c(40000, 10000, 25000, 9000, 18000)
Finland <- c(30000, 11000, 18000, 3000, 13000)
Island <- c(40000, 6000, 11000, 2000, 12000)
# industry jobs in five industries for five countries
countries <- data.frame(Norway, Denmark, Finland, Island)
# data frame with all comparison countries
krugman.spec2(Sweden, countries)
# returns the Krugman coefficient for the specialization
# of sweden compared to Norway, Denmark, Finland and Island
# 0.1595
# }