Learn R Programming

REAT (version 1.3.2)

krugman.conc:

Description

Calculating the Krugman coefficient for the spatial concentration of two industries based on regional industry data (normally employment data)

Usage

krugman.conc(e_ij, e_uj)

Arguments

e_ij
a numeric vector with the employment of the industry \(i\) in regions \(j\)
e_uj
a numeric vector with the employment of the industry \(u\) in region \(j\)

Value

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

Details

The Krugman coefficient of industry concentration (\(K_{iu}\)) is a measure for the dissimilarity of the spatial structure of two industries (\(i\) and \(u\)) 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).

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.conc2, krugman.spec, krugman.spec2, locq

Examples

Run this code
E_ij <- c(4388, 37489, 129423, 60941)
E_uj <- E_ij/2
krugman.conc(E_ij, E_uj)
# exactly the same structure (= no concentration)

Run the code above in your browser using DataLab