educineq: Compute and Decompose Inequality in Education

Easily compute education inequality measures and the distribution of educational attainments for any group of countries, using the data set developed in Jorda, V. and Alonso, JM. (2017) <doi:10.1016/j.worlddev.2016.10.005>. The package offers the possibility to compute not only the Gini index, but also generalized entropy measures for different values of the sensitivity parameter. In particular, the package includes functions to compute the mean log deviation, which is more sensitive to the bottom part of the distribution; the Theil’s entropy measure, equally sensitive to all parts of the distribution; and finally, the GE measure when the sensitivity parameter is set equal to 2, which gives more weight to differences in higher education. The decomposition of these measures in the components between-country and within-country inequality is also provided. Two graphical tools are also provided, to analyse the evolution of the distribution of educational attainments: The cumulative distribution function and the Lorenz curve.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: ineq, flexsurv
Published: 2017-02-17
DOI: 10.32614/CRAN.package.educineq
Author: Vanesa Jorda [aut, cre], Jose Manuel Alonso [aut]
Maintainer: Vanesa Jorda <jordav at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: educineq results


Reference manual: educineq.pdf


Package source: educineq_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): educineq_0.1.0.tgz, r-oldrel (arm64): educineq_0.1.0.tgz, r-release (x86_64): educineq_0.1.0.tgz, r-oldrel (x86_64): educineq_0.1.0.tgz


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