REAT (version 1.3.1)

gini.spec:

Description

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

Usage

gini.spec(e_ij, e_i)

Arguments

e_ij

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

e_i

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

Value

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

Details

The Gini coefficient of regional specialization (\(G_{j}\)) is a special spatial modification of the Gini coefficient of inequality (see the function gini()). It represents the degree of regional specialization of the region \(j\) referring to \(i\) industries. The coefficient \(G_{j}\) varies between 0 (no specialization) and 1 (complete specialization).

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.conc

Examples

# Example from Farhauer/Kroell (2013):
E_ij <- c(700,600,500,10000,40000)
# employment of five industries in the region
E_i <- c(30000,15000,10000,60000,50000)
# over-all employment in the five industries
gini.spec (E_ij, E_i)
# Returns the Gini coefficient of regional specialization (0.6222222)

# Example Freiburg
data(Freiburg)
# Loads the data
E_ij <- Freiburg$e_Freiburg2014
# industry-specific employment in Freiburg 2014
E_i <- Freiburg$e_Germany2014
# industry-specific employment in Germany 2014
gini.spec (E_ij, E_i)
# Returns the Gini coefficient of regional specialization (0.2089009)