REAT (version 1.3.2)

krugman.spec2:

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

# 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