REAT (version 3.0.3)

conc: Measures of industry concentration

Description

Calculating three measures of industry concentration (Gini, Krugman, Hoover) for a set of \(I\) industries

Usage

conc(e_ij, industry.id, region.id, na.rm = TRUE)

Arguments

e_ij

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

industry.id

a vector containing the IDs of the industries \(i\)

region.id

a vector containing the IDs of the regions \(j\)

na.rm

logical argument that indicates whether NA values should be excluded before computing results

Value

A matrix with three columns (Gini coefficient, Krugman coefficient, Hoover coefficient) and \(I\) rows (one for each regarded industry).

Details

This function is a convenient wrapper for all functions calculating measures of spatial concentration of industries (Gini, Krugman, Hoover)

References

Farhauer, O./Kroell, A. (2014): “Standorttheorien: Regional- und Stadtoekonomik in Theorie und Praxis”. Wiesbaden : Springer.

Schaetzl, L. (2000): “Wirtschaftsgeographie 2: Empirie”. Paderborn : Schoeningh.

See Also

gini.conc, krugman.conc2, hoover

Examples

# NOT RUN {
data(G.regions.industries)

conc_i <- conc (e_ij = G.regions.industries$emp_all, 
industry.id = G.regions.industries$ind_code,
region.id = G.regions.industries$region_code)
# }