# gini.spec: Gini coefficient of regional specialization In REAT: Regional Economic Analysis Toolbox

## Description

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

## Usage

 ```1 2 3 4 5 6 7``` ```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))

## 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`).

## Value

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

Thomas Wieland

## 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.

`gini`, `gini.conc`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```# 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) ```

### Example output

``` 0.6222222
 0.2089009
 0.359852
```

REAT documentation built on Nov. 21, 2019, 5:08 p.m.