REAT (version 3.0.2)

hoover: Hoover Concentration Index

Description

Calculating the Hoover Concentration Index with respect to regional income (e.g. GDP) and population

Usage

hoover(x, ref = NULL, weighting = NULL, output = "HC", na.rm = TRUE)

Arguments

x

A numeric vector (dataset of regional income, e.g. GDP)

ref

A numeric vector containing the reference distribution for the Hoover Index, e.g. population. If reg = NULL, the reference distribution is set to \(1/n\)

weighting

A numeric containing the weightings for the Hoover Index, e.g. population

output

Default option is the output of the Hoover Index. If output = "data", the corresponding data table is returned instead

na.rm

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

Value

A single numeric value of the Hoover Concentration Index (\(0 < CI < 1\)).

Details

The Hoover Concentration Index (\(CI\)) measures the economic concentration of income across space by comparing the share of income (e.g. GDP - Gross Domestic Product) with the share of population. The index varies between 0 (no inequality/concentration) and 1 (complete inequality/concentration). It can be used for economic inequality and/or regional disparities (Huang/Leung 2009).

References

Bahrenberg, G./Giese, E./Mevenkamp, N./Nipper, J. (2010): “Statistische Methoden in der Geographie. Band 1: Univariate und bivariate Statistik”. Stuttgart: Borntraeger.

Huang, Y./Leung, Y. (2009): “Measuring Regional Inequality: A Comparison of Coefficient of Variation and Hoover Concentration Index”. In: In: The Open Geography Journal, 2, p. 25-34.

Portnov, B.A./Felsenstein, D. (2010): “On the suitability of income inequality measures for regional analysis: Some evidence from simulation analysis and bootstrapping tests”. In: Socio-Economic Planning Sciences, 44, 4, p. 212-219.

See Also

cv, gini, herf, theil, atkinson, coulter, disp

Examples

# NOT RUN {
# Regional disparities in Germany:
gdp <- c(460.69, 549.19, 124.16, 65.29, 31.59, 109.27, 263.44, 39.87, 258.53, 
645.59, 131.95, 35.03, 112.66, 56.22, 85.61, 56.81)
# GDP of german regions 2015 (in billion EUR)
pop <- pop <- c(10879618, 12843514, 3520031, 2484826, 671489, 1787408, 6176172, 
1612362, 7926599, 17865516, 4052803, 995597, 4084851, 2245470, 2858714, 2170714)
# population of german regions 2015
hoover(gdp, pop)
# }