Histogram-Based Interpolation of the Lorenz Curve and Gini Index for Grouped Data
Date issued
2012
In
The American Statistician, Taylor & Francis
Vol
66
No
4
From page
225
To page
231
Subjects
Binning Class intervals Income distribution Inequality
Abstract
In grouped data, the estimation of the Lorenz curve without taking into account the within-class variability leads to an overestimation of the curve and an underestimation of the Gini index. We propose a new strictly convex estimator of the Lorenz curve derived from a linear interpolation-based approximation of the cumulative distribution function. Integrating the Lorenz curve, a correction can be derived for the Gini index that takes the intraclass variability into account.
Publication type
journal article
File(s)![Thumbnail Image]()
Loading...
Name
Till_Y.-Histogram-based-20170602.pdf
Type
Main Article
Size
128.09 KB
Format
Adobe PDF
