gini {binsmooth} | R Documentation |
Estimates the Gini coefficient from a smoothed distribution.
gini(binFit)
binFit |
A list as returned by |
For distributions of non-negative support, the Gini coefficient can be computed from a cumulative distribution function F(x) by the integral
G = 1 - \frac{1}{μ}\int_0^∞ (1-F(x))^2 \, dx
where μ is the mean of the distribution.
Returns the Gini coefficient G.
David J. Hunter and McKalie Drown
Paul T. von Hippel, David J. Hunter, McKalie Drown. Better Estimates from Binned Income Data: Interpolated CDFs and Mean-Matching, Sociological Science, November 15, 2017. https://www.sociologicalscience.com/articles-v4-26-641/
# 2005 ACS data from Cook County, Illinois binedges <- c(10000,15000,20000,25000,30000,35000,40000,45000, 50000,60000,75000,100000,125000,150000,200000,NA) bincounts <- c(157532,97369,102673,100888,90835,94191,87688,90481, 79816,153581,195430,240948,155139,94527,92166,103217) stepfit <- stepbins(binedges, bincounts, 76091) splinefit <- splinebins(binedges, bincounts, 76091) gini(stepfit) gini(splinefit) # More accurate