| gini.w {affluenceIndex} | R Documentation |
Gini coefficient
Description
Computes the Gini coefficient.
Usage
gini.w(x, weight)
Arguments
x |
income vector of population |
weight |
vector of weights |
Details
The Gini coefficient is the most popular measure of income inequality. The formula taking into account the weights of income w_1,w_2,...,w_n is given by:
G_w = \frac{\sum_{i=1}^nw_i\sum_{j=1}^n w_j|x_i-x_j|}{2(\sum_{i=1}^nw_i)^2\mu_w},
where x_i,x_j are incomes of individuals i and j, respectively, n is the number of individuals, \mu_w is the mean income. The Gini coefficient ranges between 1 (perfect equality) and 1 (perfect inequality).
Value
GG |
the value of coefficient |
Author(s)
Alicja Wolny-Dominiak, Anna Saczewska-Piotrowska
References
1. Creedy J. (2015). A note on computing the Gini inequality measure with weighted data. Workin Paper No. 3, Victoria University of Wellington.
2. Lerman R.I., Yitzhaki S. (1989) Improving the accuracy of estimates of Gini coefficients. Journal of Econometrics, 42(1), pp. 43-47.
Examples
data(affluence)
gini.w(affluence$income, affluence$hs_size)