REAT (version 3.0.2)

gini.spec: Gini coefficient of regional specialization

Description

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

Usage

gini.spec(e_ij, e_i, lc = FALSE, lcx = "% of objects", 
lcy = "% of regarded variable", lctitle = "Lorenz curve", 
le.col = "blue", lc.col = "black", lsize = 1, ltype = "solid",
bg.col = "gray95", bgrid = TRUE, bgrid.col = "white", 
bgrid.size = 2, bgrid.type = "solid", lcg = FALSE, lcgn = FALSE, 
lcg.caption = NULL, lcg.lab.x = 0, lcg.lab.y = 1, 
add.lc = FALSE, plot.lc = TRUE)

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 $i$

lc

logical argument that indicates if the Lorenz curve is plotted additionally (default: lc = FALSE, so no Lorenz curve is displayed)

lcx

if lc = TRUE (plot of Lorenz curve), lcx defines the x axis label

lcy

if lc = TRUE (plot of Lorenz curve), lcy defines the y axis label

lctitle

if lc = TRUE (plot of Lorenz curve), lctitle defines the overall title of the Lorenz curve plot

le.col

if lc = TRUE (plot of Lorenz curve), le.col defines the color of the diagonale (line of equality)

lc.col

if lc = TRUE (plot of Lorenz curve), lc.col defines the color of the Lorenz curve

lsize

if lc = TRUE (plot of Lorenz curve), lsize defines the size of the lines (default: 1)

ltype

if lc = TRUE (plot of Lorenz curve), ltype defines the type of the lines (default: "solid")

bg.col

if lc = TRUE (plot of Lorenz curve), bg.col defines the background color of the plot (default: "gray95")

bgrid

if lc = TRUE (plot of Lorenz curve), the logical argument bgrid defines if a grid is shown in the plot

bgrid.col

if lc = TRUE (plot of Lorenz curve) and bgrid = TRUE (background grid), bgrid.col defines the color of the background grid (default: "white")

bgrid.size

if lc = TRUE (plot of Lorenz curve) and bgrid = TRUE (background grid), bgrid.size defines the size of the background grid (default: 2)

bgrid.type

if lc = TRUE (plot of Lorenz curve) and bgrid = TRUE (background grid), bgrid.type defines the type of lines of the background grid (default: "solid")

lcg

if lc = TRUE (plot of Lorenz curve), the logical argument lcg defines if the non-standardized Gini coefficient is displayed in the Lorenz curve plot

lcgn

if lc = TRUE (plot of Lorenz curve), the logical argument lcgn defines if the standardized Gini coefficient is displayed in the Lorenz curve plot

lcg.caption

if lcg = TRUE (displaying the Gini coefficient in the plot), lcg.caption specifies the caption above the coefficients

lcg.lab.x

if lcg = TRUE (displaying the Gini coefficient in the plot), lcg.lab.x specifies the x coordinate of the label

lcg.lab.y

if lcg = TRUE (displaying the Gini coefficient in the plot), lcg.lab.y specifies the y coordinate of the label

add.lc

if lc = TRUE (plot of Lorenz curve), add.lc specifies if a new Lorenz curve is plotted (add.lc = "FALSE") or the plot is added to an existing Lorenz curve plot (add.lc = "TRUE")

plot.lc

logical argument that indicates if the Lorenz curve itself is plotted (if plot.lc = FALSE, only the line of equality is plotted))

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). Optionally a Lorenz curve is plotted (if lc = TRUE).

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

# NOT RUN {
# 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)

# Example Goettingen
data(Goettingen)
# Loads the data
gini.spec(Goettingen$Goettingen2017[2:16], Goettingen$BRD2017[2:16])
# Returns the Gini coefficient of regional specialization 2017 (0.359852)
# }