gini: Estimate the Gini coefficient
In binsmooth: Generate PDFs and CDFs from Binned Data

Description Usage Arguments Details Value Author(s) References Examples

View source: R/gini.R

Estimates the Gini coefficient from a smoothed distribution.

1	gini(binFit)

binFit

A list as returned by splinebins, stepbins, or rsubbins. (Alternatively, a list containing a PDF of non-negative support, its CDF, and an upper bound for the support of the PDF.)

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