disp: Concentration/inequality/dispersion measures

In REAT: Regional Economic Analysis Toolbox

Description

Calculating a set of concentration/inequality/dispersion measures

Usage

disp(x, weighting = NULL, at.epsilon = 0.5, na.rm = TRUE)

Arguments

x	a numeric vector or matrix or columns from a data frame
weighting	a weighting vector, e.g. population
at.epsilon	Weighting parameter ε for the Atkinson index
na.rm	logical argument that indicates whether NA values should be excluded before computing results

Details

This function is a convenient wrapper for all functions calculating concentration/inequality measures.

Value

A matrix containing the concentration/inequality measures.

Author(s)

Thomas Wieland

References

Gluschenko, K. (2018): “Measuring regional inequality: to weight or not to weight?” In: Spatial Economic Analysis, 13, 1, p. 36-59.

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

atkinson, coulter, dalton, cv, gini2, herf, hoover, sd2, theil, williamson

Examples

data(Automotive)

disp(Automotive$Turnover2008)
disp(Automotive[4:8])

REAT documentation built on Sept. 5, 2021, 5:18 p.m.