Atkinson: Atkinson Index of Inequality
In SciencesPo: A Tool Set for Analyzing Political Behavior Data

Description Usage Arguments Details References See Also Examples

Calculates the Atkinson index A. This inequality measure is especially good at determining which end of the distribution is contributing most to the observed inequality.

Atkinson(x, n = rep(1, length(x)), epsilon = NULL, na.rm = FALSE, ...)

## Default S3 method:
Atkinson(x, n = rep(1, length(x)), epsilon = NULL,
  na.rm = FALSE, ...)

`x`	a vector of data values of non-negative elements.
`n`	a vector of frequencies of the same length as `x`.
`epsilon`	a parameter of the inequality measure (if `NULL`, the default parameter (0.5) of the respective measure is used).
`na.rm`	logical. Should missing values be removed? Defaults is set to `FALSE`.
`...`	additional arguements (currently ignored)

epsilon = 0,5: little inequality aversion epsilon = 1,0: medium inequality aversion epsilon = 2,0: great inequality aversion

Cowell, F. A. (2000) Measurement of Inequality in Atkinson, A. B. / Bourguignon, F. (Eds): Handbook of Income Distribution. Amsterdam.

Cowell, F. A. (1995) Measuring Inequality Harvester Wheatshef: Prentice Hall.

Herfindahl, Rosenbluth, Gini. For more details see the “Indices” vignette.

if (interactive()) {
# generate a vector (of incomes)
# y <- c(80, 60, 10, 20, 30)
# Entropy 1.392321
# Maximum Entropy	1.609438
# Normalized Entropy	0.865098
# Exponential Index	0.248498
# Herfindahl	0.285000
# Normalized Herfindahl	0.106250
# Gini Coefficient	0.360000
# Concentration Coefficient	0.450000

x <- c(778, 815, 857, 888, 925, 930, 965, 990, 1012)

# compute Atkinson coefficient with epsilon=0.5
Atkinson(x, epsilon=0.5)

w <- c(10, 15, 20, 25, 40, 20, 30, 35, 45, 90)
}