REAT (version 1.3.1)

gini.conc:

Description

Calculating the Gini coefficient of spatial industry concentration based on regional industry data (normally employment data)

Usage

gini.conc(e_ij, e_j)

Arguments

e_ij

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

e_j

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

Value

A single numeric value (\(0 < G_{i} < 1\))

Details

The Gini coefficient of spatial industry concentration (\(G_{i}\)) is a special spatial modification of the Gini coefficient of inequality (see the function gini()). It represents the rate of spatial concentration of the industry \(i\) referring to \(j\) regions (e.g. cities, counties, states). The coefficient \(G_{i}\) varies between 0 (perfect distribution, respectively no concentration) and 1 (complete concentration in one region).

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, gini.spec

Examples

# Example from Farhauer/Kroell (2013):
E_ij <- c(500,500,1000,7000,1000)
# employment of the industry in five regions
E_j <- c(20000,15000,20000,40000,5000)
# employment in the five regions
gini.conc (E_ij, E_j)
# Returns the Gini coefficient of industry concentration (0.4068966)